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Doctoral Programs in Computational Science and Engineering

Application & admission information.

The Center for Computational Science and Engineering (CCSE) offers two doctoral programs in computational science and engineering (CSE) – one leading to a standalone PhD degree in CSE offered entirely by CCSE ( CSE PhD ) and the other leading to an interdisciplinary PhD degree offered jointly with participating departments in the School of Engineering and the School of Science ( Dept-CSE PhD ).

While both programs enable students to specialize at the doctoral level in a computation-related field via focused coursework and a thesis, they differ in essential ways. The standalone CSE PhD program is intended for students who plan to pursue research in cross-cutting methodological aspects of computational science. The resulting doctoral degree in Computational Science and Engineering is awarded by CCSE via the the Schwarzman College of Computing. In contrast, the interdisciplinary Dept-CSE PhD program is intended for students who are interested in computation in the context of a specific engineering or science discipline. For this reason, this degree is offered jointly with participating departments across the Institute; the interdisciplinary degree is awarded in a specially crafted thesis field that recognizes the student’s specialization in computation within the chosen engineering or science discipline.

Applicants to the standalone CSE PhD program are expected to have an undergraduate degree in CSE, applied mathematics, or another field that prepares them for an advanced degree in CSE. Applicants to the Dept-CSE PhD program should have an undergraduate degree in a related core disciplinary area as well as a strong foundation in applied mathematics, physics, or related fields. When completing the MIT CSE graduate application , students are expected to declare which of the two programs they are interested in. Admissions decisions will take into account these declared interests, along with each applicant’s academic background, preparation, and fit to the program they have selected.  All applicants are asked to specify MIT CCSE-affiliated faculty that best match their research interests; applicants to the Dept-CSE PhD program also select the home department(s) that best match. At the discretion of the admissions committee, Dept-CSE PhD applications might also be shared with a home department beyond those designated in the application. CSE PhD admissions decisions are at the sole discretion of CCSE; Dept-CSE PhD admission decisions are conducted jointly between CCSE and the home departments.

Please note: These are both doctoral programs in Computational Science and Engineering; applicants interested in Computer Science must apply to the Department of Electrical Engineering and Computer Science .

Important Dates

September 15: Application Opens December 1: Deadline to apply for admission* December – March: Application review period January – March: Decisions released on rolling basis

*All supplemental materials (e.g., transcripts, test scores, letters of recommendation) must also be received by December 1. Application review begins on that date, and incomplete applications may not be reviewed. Please be sure that your recommenders are aware of this hard deadline, as we do not make exceptions. We also do not allow students to upload/submit material beyond what is required, such as degree certificates, extra recommendations, publications, etc.

A complete electronic CSE application includes the following:

• Three letters of recommendation ;
• Students admitted to the program will be required to supply official transcripts. Discrepancies between unofficial and official transcripts may result in the revocation of the admission offer.
• Statement of objectives (limited to approximately one page) and responses to department-specific prompts for Dept-CSE PhD applicants;
• Official GRE General Test score report , sent to MIT by ETS via institute code 3514 GRE REQUIREMENT WAIVED FOR FALL 2025 ;
• Official IELTS score report sent to MIT by IELTS†  (international applicants from non-English speaking countries only; see below for more information)
• Resume or CV , uploaded in PDF format;
• MIT graduate application fee of $75‡.

‡Application Fee

The MIT graduate application fee of $75.00 is a mandatory requirement set by the Institute payable by credit card. Please visit the MIT Graduate Admission Application Fee Waiver page for information about fee waiver eligibility and instructions.

Please note: CCSE cannot issue fee waivers; email requests for fee waivers sent to [email protected] will not receive a response.

Admissions Contact Information

Email: [email protected]

► Current MIT CSE SM Students: Please see the page for Current MIT Graduate Students .

GRE Requirement

GRE REQUIREMENT WAIVED FOR FALL 2025 All applicants are required to take the Graduate Record Examination (GRE) General Aptitude Test. The MIT code for submitting GRE score reports is 3514 (you do not need to list a department code). GRE scores must current; ETS considers scores valid for five years after the testing year in which you tested.

†English Language Proficiency Requirement

The CSE PhD program requires international applicants from non-English speaking countries to take the academic  version of the International English Language Testing System (IELTS).  The IELTS exam measures one’s ability to communicate in English in four major skill areas: listening, reading, writing, and speaking.  A minimum IELTS score of 7 is required for admission.  For more information about the IELTS, and to find out where and how to take the exam, please visit the IELTS web site .

While we will also accept the TOEFL iBT (Test of English as a Foreign Language), we strongly prefer the IELTS. The minimum TOEFL iBT score is 100.

This requirement is waived for those who can demonstrate that one or more of the following are true:

• English is/was the language of instruction in your four-year undergraduate program,
• English is the language of your employer/workplace for at least the last four years,
• English was your language of instruction in both primary and secondary schools.

Degree Requirements for Admission

To be admitted as a regular graduate student, an applicant must have earned a bachelor’s degree or its equivalent from a college, university, or technical school of acceptable standing. Students in their final year of undergraduate study may be admitted on the condition that their bachelor’s degree is awarded before they enroll at MIT.

Applicants without an SM degree may apply to the CSE PhD program, however, the Departments of Aeronautics and Astronautics and Mechanical Engineering nominally require the completion of an SM degree before a student is considered a doctoral candidate. As a result, applicants to those departments holding only a bachelor’s degree are asked in the application to indicate whether they prefer to complete the CSE SM program or an SM through the home department.

Nondiscrimination Policy

The Massachusetts Institute of Technology is committed to the principle of equal opportunity in education and employment.  To read MIT’s most up-to-date nondiscrimination policy, please visit the Reference Publication Office’s nondiscrimination statement page .

Additional Information

For more details, as well as answers to most commonly asked questions regarding the admissions process to individual participating Dept-CSE PhD departments including details on financial support, applicants are referred to the website of the participating department of interest.

Doctoral Degree in Computer Science

Carnegie Mellon's Ph.D. in Computer Science is, above all, a research degree. When the faculty award a Ph.D., they certify that the student has a broad foundation and awareness of core concepts in computer science, has advanced the field by performing significant original research and has reported that work in a scholarly fashion.

When you begin our Ph.D. program, you’ll take the Introductory Course for Doctoral Students — an intense two week program that orients you to the department, introduces you to research and education topics our faculty are interested in, helps you find a faculty advisor and familiarizes you with Carnegie Mellon’s resources. Next, you’ll gain a broad understanding of fundamental research issues in major areas of computer science through coursework and original research. Finally, you’ll write and orally defend a thesis that guarantees you understand the area well enough to advance the state of knowledge in the field.

During the first two years of the program, you’ll gain the foundation of knowledge that will allow you to become an expert researcher in computer science, primarily by

Mastering a body of graduate material, achieved by passing 96 university units worth of graduate courses (equivalent to eight full-time courses).

Learning how to organize and begin to carry out original research, achieved by participating in directed research.

You will also serve as a teaching assistant, hone your writing and speaking skills and maintain your programming prowess. You’ll also receive periodic evaluation of your progress, and must make satisfactory progress to continue in the program.

Time Commitment:

As a Ph.D. student in computer science at CMU, you'll spend roughly five years acquiring a body of technical knowledge that includes a familiarity with the breadth of the field, as well as a deep understanding of your research area. From your second month in the program, you'll work closely with your faculty advisor, who is charged with guiding your education and monitoring your progress through the program. You'll take courses, teach and perform directed research — all to ensure that you leave Carnegie Mellon as an expert in your field. For a complete breakdown of our program requirements, read our Ph.D. Handbook .

Financial Information:

The Computer Science Department offers all Ph.D. students full financial support while they are in good academic standing in their respective programs. To learn more about Ph.D. funding, visit the SCS  Doctoral Programs  webpage.

Graduate Tuition: https://www.cmu.edu/sfs/tuition/graduate/scs.html

Student Fees: https://www.cmu.edu/sfs/tuition/fees/index.html

Carnegie Mellon Graduate Student Financial Aid: https://www.cmu.edu/sfs/financial-aid/graduate/index.html

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PhD Program Admissions

Applying to our PhD Program

We’re thrilled that you are interested in our PhD program in computer science! This page provides an overview of the application process, some guidelines, and answers to specific questions. Please check our FAQ before emailing [email protected] with any questions not answered here.

Our program accepts a large number of applicants each year from a diverse range of backgrounds. Our applicants come directly from undergraduate or master’s programs, as well as industry positions, and from within United States and numerous countries around the world.

Visit the interactive PhD program statistics page   to view historical program data pertaining to admissions, enrollment, retention/attrition/completion, and time to degree conferral. (Select “ Computer Science” from the “Choose Program” drop-down menu.)

Ready to start your PhD application?

We’re ready for you. Click on the link below to start your application to become a PhD student at Johns Hopkins University

The Application: General Advice

The most important question we ask when reviewing applications is "Will this individual excel at research?" Every part of your application is helpful insofar as it answers this question. The three major components of an application are the statement, letters of recommendation, and grades.

This is one of the most important parts of your application; it lets us get to know you and creates a narrative of your academic career and future plans. Before you write your statement, start by thinking about what you want us to learn about you. Make a list of important achievements, perspectives, and goals. Build your statement around this list. We are looking for students who have made the most of the opportunities they have been presented with and who are smart, creative, and motivated. Keep in mind that we also have your CV and letters of recommendation, so we don’t necessarily need a list of all your accomplishments. However, your statement can fill in the narrative around what you did and, more specifically, why you did it. What motivates you? What are your research interests and why? These details aren’t found elsewhere in your application, so focus on them in your statement.

There are a few things we suggest not including in your statement. While it’s tempting to give a rationale for why you are applying to our program, don’t include it if it’s uninformed. Consider: “I want to apply to Johns Hopkins because it’s one of the premiere academic programs.” We know that already! If you do have specific reasons to be interested in our program (e.g. location, a specific project, a faculty member, etc.), be sure to mention them.

In terms of your motivation, be specific! Don’t write: “I’ve wanted to do a PhD in CS since I was six years old.” We don’t trust that six-year-olds make good career decisions. If you write “I have always found AREA X fascinating,” explain why.

Letters of Recommendation

The two most important factors of a recommendation letter are: 1) select someone who knows you well, and 2) select someone who knows how to write a letter.

First, it’s tempting to ask Professor X. to write a letter for you because they are a well-known person in the field. While we can better contextualize letters from people we know, it’s only helpful if the letter contains meaningful information. If Professor X. writes, “I’ve met the applicant a few times and they seem sharp,” that’s not useful information. It’s more important to select someone who knows you well and can discuss your achievements in detail.

Second, your letter writer should know how to write a letter. Academic research programs look for different things than a company. We often read letters from work supervisors that say nice things, but don’t speak to the qualities we find most important.

Of course, it’s a balance. You want someone who knows you well, but they still need to know how to write a good letter of recommendation.

We understand that three letters are a lot, especially for an undergraduate applying directly to a PhD program. We don’t expect each candidate to have three amazing letters. Your choices should be about balance: you want people who know you well, can write good academic letters, and know the research field. Use your choice of your three letter-writers to create this balance.

There isn’t much you can do about your grades—you have the grades you have. However, we do not use any grade cutoffs or thresholds in admissions. We want to see that you did well and excelled in whatever program you were in. Did you push yourself to take upper-level classes? Did you do well in the classes most directly related to your research area? If you have special circumstances that explain some of your grades, please include a description of them in your statement.

The Whiting School of Engineering does not require GRE General Test scores for applications to our PhD programs.

TOEFL or IELTS

Non-native English speakers must take the TOEFL or IELTS exams. Details on accepted exams, scores, and exceptions to this requirement can be found here .

Application Tips

There are many helpful guides for PhD applications. Here are a few we recommend:

• How to be a Successful PhD Student (co-authored by our own Mark Dredze )
• What Readers Look for in a Statement of Purpose
• Student Perspectives on Applying to NLP PhD Programs
• A Survival Guide to a PhD

Application Deadlines

Application Deadline:

The deadline for fall is December 15th. (No recruiting for spring admissions.)

The application will be available for submission on or around August 15.

Vivien Thomas Scholars

The Vivien Thomas Scholars Initiative (VTSI) is an endowed fellowship program at Johns Hopkins for PhD students in STEM fields. It provides full tuition, stipend, and benefits while also providing targeted mentoring, networking, community, and professional development opportunities. Students who have attended a historically black college and university or other minority serving institution for undergraduate study are eligible to apply. To be considered for the VTSI, all application and supplementary materials must be received by December 1, 2021.

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Computer Science, Ph.D.

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We have a thriving Ph.D. program with approximately 80 full-time Ph.D. students hailing from all corners of the world. Most full-time Ph.D. students have scholarships that cover tuition and provide a monthly stipend. Admission is highly competitive. We seek creative, articulate students with undergraduate and master's degrees from top universities worldwide. Our  current research strengths  include data management and analysis, cybersecurity, computer games, visualization, web search, graphics, vision and image processing, and theoretical computer science.

This degree program offers interested students opportunities to do their research abroad, under the supervision of faculty at NYU Shanghai or  NYU Abu Dhabi .

• View the Computer Science Ph.D. program flyer
• Admissions requirements for the Ph.D. Program.
• Find out more about general  Admission Requirements .

To receive a Ph.D. in Computer Science at the NYU Tandon School of Engineering, a student must:

• satisfy a breadth course requirement, intended to ensure broad knowledge of computer science,
• satisfy a depth requirement, consisting of an oral qualifying exam presentation with a written report, to ensure the student's ability to do research,
• submit a written thesis proposal and make an oral presentation about the proposal,
• write a Ph.D. thesis that must be approved by a dissertation guidance committee and present an oral thesis defense, and
• satisfy all School of Engineering requirements for the Ph.D. degree, as described in the NYU Tandon School of Engineering bulletin, including graduate study duration, credit points, GPA, and time-to-degree requirements.

Upon entering the program, each student will be assigned an advisor who will guide them in formulating an individual study plan directing their course choice for the first two years. The department will hold an annual Ph.D. Student Assessment Meeting, in which all Ph.D. students will be formally reviewed.

Note: for pre-fall 2015 Ph.D. students, please see the pre-fall 2015 Ph.D. Curriculum.

Program Requirements

Details about Breadth and Depth Requirements, Thesis Proposal and Presentation, and Thesis Defense can be found in the NYU Bulletin.

Program Details

Each incoming Ph.D. student will be assigned to a research advisor, or to an interim advisor, who will provide academic advising until the student has a research advisor. The advisor will meet with the student when the student enters the program to guide the student in formulating an Individual Study Plan. The purpose of the plan is to guide the student’s course choice for the first two years in the program and to ensure that the student meets the breadth requirements. The plan may also specify additional courses to be taken by the student in order to acquire necessary background and expertise. Subsequent changes to the plan must be approved by the advisor.

Sample Plan of Study

In order to obtain a Ph.D. degree, a student must complete a minimum of 75 credits of graduate work beyond the BS degree, including at least 21 credits of dissertation. A Master of Science in Computer Science may be transferred as 30 credits without taking individual courses into consideration. Other graduate coursework in Computer Science may be transferred on a course-by-course basis. Graduate coursework in areas other than Computer Science can be transferred on a course-by-course basis with approval of the Ph.D. Committee (PHDC). The School of Engineering places some limits on the number and types of transfer credits that are available. Applications for transfer credits must be submitted for consideration before the end of the first semester of matriculation. 

All Ph.D. students will be formally reviewed each year in a Ph.D. Student Assessment Meeting. The review is conducted by the entire CSE faculty and includes at least the following items (in no particular order):

• All courses taken, grades received, and GPAs.
• Research productivity: publications, talks, software, systems, etc.
• Faculty input, especially from advisors and committee members.
• Student’s own input.
• Cumulative history of the student's progress.

As a result of the review, each student will be placed in one of the following two categories, by vote of the faculty:

• In Good Standing: The student has performed well in the previous semester and may continue in the Ph.D. program for one more year, assuming satisfactory academic progress is maintained.
• Not in Good Standing: The student has not performed sufficiently well in the previous year. The consequences of not being in good standing will vary, and may include being placed on probation, losing RA/GA/TA funding, or not being allowed to continue in the Ph.D. program.

Following the review, students will receive formal letters which will inform them of their standing. The letters may also make specific recommendations to the student as to what will be expected of them in the following year. A copy of each student’s letter will be placed in the student’s file.

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PhD in Computer Science

Our doctoral program is a full-time program: Admitted doctoral students have only the Ph.D. as their degree objective, and they have guaranteed funding for up to five years.

GRE Not Required for the Fall 2025 cycle

Please note: students applying to graduate programs in Fall 2025 are not required to take the GRE. The same holds for students applying for the 4+1 programs.

Applying to the PhD Program

2025 admission requirements.

Questions about our PhD program should be directed by email to [email protected] .

The required components of your application are:

• The online application form
• Three (3) letters of recommendation
• All applicants should upload a scanned copy of their transcripts.  Applicants should not send an official transcript to the Graduate Office unless they are admitted and accept our offer of Admission.
• TOEFL or IELTS scores (required for non-native English speakers, photocopy accepted, original required upon admission)
• The $40 application fee

These items must reach us by December 15, 2024  in order for your application to receive full consideration.

If English is not your native language, we require that you take the TOEFL (Test Of English as a Foreign Language) or the IELTS (International English Language Testing System exam). An IELTS band score of 7.0 or above is required for Dartmouth Programs, but we have no specific test score requirements for the TOEFL or GRE. If you are transferring from a U.S. university, we may waive the language test. As with the GRE, we will accept a photocopy until the official report is available, but the photocopy must reach us by  December  15, 2024 .

We prefer that your recommenders provide their recommendations online. Once you have listed their names on the application, an email will be sent to them with a link to the application site. If necessary, we will also accept recommendations in sealed envelopes through the mail.

We require a $40.00 application fee, to be paid by credit card online. The fee helps to cover the cost of processing your application and is non-refundable. The application fee will not be waived.

Like many graduate programs, we base our admissions decisions primarily on the information requested above. We have no minimum test scores. We recognize that you may have talents and experience that do not shine through the forms and test scores.

Use the Application Essay section of the online application to give additional information. Do you have a specific reason for coming to Dartmouth? Specific goals for your study? Significant work experience? Why do you want to do advanced training in computer science? Include any publications you have authored.

In the Computer Science Supplement section of the online application, attach examples of your work. This is also the place where you can attach a resume.

At the discretion of the admissions committee, we award stipends as well as tuition grants without stipend. The stipend awards cover tuition waiver and a payment for living expenses for nine months of each year for five years, as long as satisfactory progress is made toward the Ph.D. The stipend for 2023-2024 is $3,333.33 per month, and it generally increases every year. Health insurance cost for the academic year is covered by the college for full-time students. Graduate students who receive support contribute to the program by teaching or grading undergraduate courses, assisting with advanced courses, and participating in research projects. Additional stipend is provided for the summer months if the student performs research or teaching assistance during that period.

There is no separate application for financial aid. Every applicant is considered for financial aid, unless you say that you do not need financial support. If you do not need support, please indicate this on the application form, and tell us how you expect to be supported.

Frequently Asked Questions

Answers to additional FAQs about grad admissions, including how to obtain a fee waiver, update an application, and waive TOEFL based on a degree from an English institution, are available at the grad school site .

Q. What are the institution and department codes for the GRE? A. The GRE institution code is 3351, and the GRE department code is 0402.

Q. What are the institution and department codes for the TOEFL? A. The TOEFL institution code is 3351, and the TOEFL department code is 78.

Q. If my GRE scores are low, but I have good grades, can I still get admission? A. Our decision takes into account all components of your application. Therefore, it is usually impossible to predict the outcome until you apply and the admissions committee goes over your entire application.

Q. Can I be admitted for the Winter term? A. No. We only admit one class each year, matriculating in the Fall term.

Q. Where should I have the transcripts and scores sent? A. Send to:      Guarini School of Graduate and Advanced Studies      Dartmouth College      Attn: Computer Science Graduate Admissions      Anonymous Hall      64 College St, Suite 6062, Room 102      Hanover NH 03755      Phone: (603) 646-8193

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Academics   /   Graduate PhD in Computer Science

The doctor of philosophy in computer science program at Northwestern University primarily prepares students to become expert independent researchers. PhD students conduct original transformational research in extant and emerging computer science topics. Students work alongside top researchers to advance the core CS fields from Theory to AI and Systems and Networking . In addition, PhD students have the opportunity to collaborate with CS+X faculty who are jointly appointed between CS and disciplines including business, law, economics, journalism, and medicine.

Joining a Track

Doctor of philosophy in computer science students follow the course requirements, qualifying exam structure, and thesis process specific to one of five tracks :

• Artificial Intelligence and Machine Learning
• Computer Engineering

Within each track, students explore many areas of interest, including programming languages , security and privacy and human-computer interaction .

Learn more about computer science research areas

Curriculum and Requirements

The focus of the CS PhD program is learning how to do research by doing research, and students are expected to spend at least 50% of their time on research. Students complete ten graduate curriculum requirements (including COMP_SCI 496: Introduction to Graduate Studies in Computer Science ), and additional course selection is tailored based on individual experience, research track, and interests. Students must also successfully complete a qualifying exam to be admitted to candidacy.

CS PhD Manual Apply now

Request More Information

Download a PDF program guide about your program of interest and get in contact with our graduate admissions staff.

Request info about the PhD degree

Opportunities for PhD Students

Cognitive science certificate.

Computer science PhD students may earn a specialization in cognitive science by taking six cognitive science courses. In addition to broadening a student’s area of study and improving their resume, students attend cognitive science events and lectures, they can receive conference travel support, and they are exposed to cross-disciplinary exchanges.

The Crown Family Graduate Internship Program

PhD candidates may elect to participate in the Crown Family Graduate Internship Program. This opportunity allows the doctoral candidate to gain practical experience in industry or in national research laboratories in areas closely related to their research.

Management for Scientists and Engineers Certificate Program

The certificate program — jointly offered by The Graduate School and Kellogg School of Management — provides post-candidacy doctoral students with a basic understanding of strategy, finance, risk and uncertainty, marketing, accounting and leadership. Students are introduced to business concepts and specific frameworks for effective management relevant to both for-profit and nonprofit sectors.

Career Paths

Recent graduates of the computer science PhD program are pursuing careers in industry & research labs, academia, and startups.

• Georgia Institute of Technology
• Illinois Institute of Technology
• Northeastern
• University of Pittsburgh
• University of Rochester
• University of Washington
• Naval Research Laboratory
• Northwestern University

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What Students Are Saying

"One great benefit of Northwestern is the collaborative effort of the CS department that enabled me to work on projects involving multiple faculty, each with their own diverse set of expertise.

Northwestern maintains a great balance: you will work on leading research at a top-tier institution, and you won't get lost in the mix."

— Brian Suchy, PhD Candidate, Computer Systems

What Alumni Are Saying

"In the early stage of my PhD program, I took several courses from the Department of Economics and the Kellogg School of Management and, later, I started collaborating with researchers in those areas. The experience taught me how to have an open mind to embrace and work with people with different backgrounds."

— Yiding Feng (PhD '21), postdoctoral researcher, Microsoft Research Lab – New England

Read an alumni profile of Yiding Feng

"My work at IBM Research involves bringing together symbolic and deep learning techniques to solve problems in interpretable, effective ways, which means I must draw upon the research I did at Northwestern quite frequently."

— Maxwell Crouse (PhD '21), AI Research Scientist, IBM Research

Read an alumni profile of Maxwell Crouse

The theory group here is very warm and close-knit. Starting a PhD is daunting, and it is comforting to have a community I can lean on.

— Vaidehi Srinivas, PhD Candidate, CS Theory

Email forwarding for @cs.stanford.edu is changing. Updates and details here .

Academics | PhD Program

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The PhD degree is intended primarily for students who desire a career in research, advanced development, or teaching. A broad Computer Science, Engineering, Science background, intensive study, and research experience in a specialized area are the necessary requisites.

The degree of Doctor of Philosophy (PhD) is conferred on candidates who have demonstrated to the satisfaction of our Department in the following areas:

• high attainment in a particular field of knowledge, and
• the ability to do independent investigation and present the results of such research.

They must satisfy the general requirements for advanced degrees, and the program requirements specified by our Department.

Program Requirements

On average, the program is completed in five to six years, depending on the student’s research and progress.

Progress Guidelines

Students should consider the progress guidelines to ensure that they are making reasonable progress.

Monitoring Progress

Annual reviews only apply to PhD students in their second year or later; yearly meetings are held for all PhD students.

CS PhD Course Guidelines

The following program guidelines (a.k.a model pogram) serve as a starting point for a discussion with the faculty about areas of interest.   This description of the Computer Science PhD course guidelines augments the school-wide  PhD course requirements .   Students should make themselves familiar with both.

Course Guidelines for Ph.D. Students in Computer Science

We expect students to obtain broad knowledge of computer science by taking graduate level courses in a variety of sub-areas in computer science, such as systems, networking, databases, algorithms, complexity, hardware, human-computer interaction, graphics, or programming languages.

Within our school, CS courses are roughly organized according to sub-area by their middle digit, so we expect students to take courses in a minimum of three distinct sub-areas, one of which should be theory (denoted by the middle digit of 2, or CS 231). Theory is specifically required as we expect all students to obtain some background in the mathematical foundations that underlie computer science. The intention is not only to give breadth to students, but to ensure cross-fertilization across different sub-disciplines in Computer Science.

Just as we expect all students obtaining a Ph.D. to have experience with the theoretical foundations of computer science, we expect all students to have some knowledge of how to build large software or hardware systems , on the order of thousands of lines of code, or the equivalent complexity in hardware. That experience may be evidenced by coursework or by a project submitted to the CHD for examination. In almost all cases a course numbered CS 26x or CS 24x will satisfy the requirement (exceptions will be noted in the course description on my.harvard). Students may also petition to use CS 161 for this requirement.   For projects in other courses, research projects, or projects done in internships the student is expected to write a note explaining the project, include a link to any relevant artifacts or outcomes, describe the student's individual contribution, and where appropriate obtain a note from their advisor, their class instructor, or their supervisors confirming their contributions.  The project must include learning about systems concepts, and not just writing many lines of code.   Students hoping to invoke the non-CS24x/26x/161 option must consult with  Prof. Mickens ,  Prof, Kung,  or  Prof. Idreos  well in advance of submitting their Program Plan to the CHD.  

Computer science is an applied science, with connections to many fields. Learning about and connecting computer science to other fields is a key part of an advanced education in computer science. These connections may introduce relevant background, or they may provide an outlet for developing new applications.

For example, mathematics courses may be appropriate for someone working in theory, linguistics courses may be appropriate for someone working in computational linguistics, economics courses may be appropriate for those working in algorithmic economics, electrical engineering courses may be appropriate for those working in circuit design, and design courses may be appropriate for someone working in user interfaces.

Requirements

The Graduate School of Arts & Sciences (GSAS) requires all Ph.D. students to complete 16 half-courses (“courses”, i.e., for 4 units of credit) to complete their degree. Of those 16 courses, a Ph.D. in Computer Science requires 10 letter-graded courses. (The remaining 6 courses are often 300-level research courses or other undergraduate or graduate coursework beyond the 10 required courses.)

The requirements for the 10 letter-graded courses are as follows:

• Of the 7 technical courses, at least 3 must be 200-level Computer Science courses, with 3 different middle digits (from the set 2,3,4,5,6,7,8), and with one of these three courses either having a middle digit of 2 or being CS 231 (i.e., a “theory” course).   Note that CS courses with a middle digit of 0 are valid technical courses, but do not contribute to the breadth requirement.
• At least 5 of the 8 disciplinary courses must be SEAS or SEAS-equivalent 200-level courses. A “SEAS equivalent” course is a course taught by a SEAS faculty member in another FAS department. 
• For any MIT course taken, the student must provide justification why the MIT course is necessary (i.e. SEAS does not offer the topic, the SEAS course has not been offered in recent years, etc.). MIT courses do not count as part of the 5 200-level SEAS/SEAS-equivalent courses. 
• 2 of the 10 courses must constitute an external minor (referred to as "breadth" courses in the SEAS “ Policies of the Committee on Higher Degrees [CHD] ”) in an area outside of computer science. These courses should be clearly related; generally, this will mean the two courses are in the same discipline, although this is not mandatory. These courses must be distinct from the 8 disciplinary courses referenced above.
• Students must demonstrate practical competence by building a large software or hardware system during the course of their graduate studies. This requirement will generally be met through a class project, but it can also be met through work done in the course of a summer internship, or in the course of research.
• In particular, for Computer Science graduate degrees, Applied Computation courses may be counted as 100-level courses, not 200-level courses.
• Up to 2 of the 10 courses can be 299r courses, but only 1 of the up to 2 allowed 299r courses can count toward the 8 disciplinary courses. 299r courses do not count toward the 5 200-level SEAS/SEAS-equivalent courses. If two 299r’s are taken, they can be with the same faculty but the topics must be sufficiently different.
• A maximum of 3 graduate-level transfer classes are allowed to count towards the 10 course requirement.
• All CS Ph.D. program plans must adhere to the SEAS-wide Ph.D. requirements, which are stated in the SEAS Policies of the Committee on Higher Degrees (CHD) . These SEAS-wide requirements are included in the items listed above, though students are encouraged to read the CHD document if there are questions, as the CHD document provides further explanation/detail on several of the items above.
• All program plans must be approved by the CHD. Exceptions to any of these requirements require a detailed written explanation of the reasoning for the exception from the student and the student’s research advisor. Exceptions can only be approved by the CHD, and generally exceptions will only be given for unusual circumstances specific to the student’s research program.

Requirement Notes

• Courses below the 100-level are not suitable for graduate credit.
• For students who were required to take it, CS 2091/2092 (formerly CS 290a/b or 290hfa/hfb may be included as one of the 10 courses but it does not count toward the 200-level CS or SEAS/SEAS-equivalent course requirements nor toward the SM en route to the PhD.

Your program plan  must always comply  with both our school's General Requirements, in addition to complying with the specific requirements for Computer Science. All program plans must be approved by the Committee on Higher Degrees [CHD]. Exceptions to the requirements can only be approved by the CHD, and generally will only be given for unusual circumstances specific to the student’s research program

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Computer Science Ph.D. Program

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The Cornell Ph.D. program in computer science is consistently ranked among the top six departments in the country, with world-class research covering all of computer science. Our computer science program is distinguished by the excellence of the faculty, by a long tradition of pioneering research, and by the breadth of its Ph.D. program. Faculty and Ph.D. students are located both in Ithaca and in New York City at the Cornell Tech campus . The Field of Computer Science also includes faculty members from other departments (Electrical Engineering, Information Science, Applied Math, Mathematics, Operations Research and Industrial Engineering, Mechanical and Aerospace Engineering, Computational Biology, and Architecture) who can supervise a student's Ph.D. thesis research in computer science.

Over the past years we've increased our strength in areas such as artificial intelligence, computer graphics, systems, security, machine learning, and digital libraries, while maintaining our depth in traditional areas such as theory, programming languages and scientific computing.  You can find out more about our research here . 

The department provides an exceptionally open and friendly atmosphere that encourages the sharing of ideas across all areas. 

Cornell is located in the heart of the Finger Lakes region. This beautiful area provides many opportunities for recreational activities such as sailing, windsurfing, canoeing, kayaking, both downhill and cross-country skiing, ice skating, rock climbing, hiking, camping, and brewery/cider/wine-tasting. In fact, Cornell offers courses in all of these activities.

The Cornell Tech campus in New York City is located on Roosevelt Island.  Cornell Tech  is a graduate school conceived and implemented expressly to integrate the study of technology with business, law, and design. There are now over a half-dozen masters programs on offer as well as doctoral studies.

FAQ with more information about the two campuses .

Ph.D. Program Structure

Each year, about 30-40 new Ph.D. students join the department. During the first two semesters, students become familiar with the faculty members and their areas of research by taking graduate courses, attending research seminars, and participating in research projects. By the end of the first year, each student selects a specific area and forms a committee based on the student's research interests. This “Special Committee” of three or more faculty members will guide the student through to a Ph.D. dissertation. Ph.D. students that decide to work with a faculty member based at Cornell Tech typically move to New York City after a year in Ithaca.

The Field believes that certain areas are so fundamental to Computer Science that all students should be competent in them. Ph.D. candidates are expected to demonstrate competency in four areas of computer science at the high undergraduate level: theory, programming languages, systems, and artificial intelligence.

Each student then focuses on a specific topic of research and begins a preliminary investigation of that topic. The initial results are presented during a comprehensive oral evaluation, which is administered by the members of the student's Special Committee. The objective of this examination, usually taken in the third year, is to evaluate a student's ability to undertake original research at the Ph.D. level.

The final oral examination, a public defense of the dissertation, is taken before the Special Committee.

To encourage students to explore areas other than Computer Science, the department requires that students complete an outside minor. Cornell offers almost 90 fields from which a minor can be chosen. Some students elect to minor in related fields such as Applied Mathematics, Information Science, Electrical Engineering, or Operations Research. Others use this opportunity to pursue interests as diverse as Music, Theater, Psychology, Women's Studies, Philosophy, and Finance.

The computer science Ph.D. program complies with the requirements of the Cornell Graduate School , which include requirements on residency, minimum grades, examinations, and dissertation.

The Department also administers a very small 2-year Master of Science program (with thesis). Students in this program serve as teaching assistants and receive full tuition plus a stipend for their services.

• MyU : For Students, Faculty, and Staff

Ph.D. in Computer Science overview

Looking to make your mark on the computer science community? Our doctoral program prepares students for careers focused on research and innovation. Whether you dream of working in the industry or in academia, a Ph.D. in computer science is the jumping off point for ground breaking discovery.

• General degree information
• Credit Requirements
• Thesis credits
• Things to remember
• Degree Progress

The Ph.D. in Computer Science is a research degree which culminates in a unique dissertation that demonstrates original and creative research. The program consists of three components: coursework, research, and thesis preparation.

Early on in your career as a graduate student, you will take courses to fulfill background, breadth and supporting program requirements. You will also take courses that help to develop and refine your research writing skills; these skills include information analysis and synthesis as well as written and verbal presentation capabilities. This part of your graduate career ends when you cross the threshold presented by the  Preliminary Oral and Written Examinations  (WPE and OPE). Taken in conjunction, these examinations serve as an early test of your research ability.

Once you have passed the WPE and OPE, you will be formally admitted to Ph.D. candidacy and are ready to begin the second phase of your career as a doctoral student. During this phase, your coursework lightens and your research increases as you focus on the definition and pursuit of your specific thesis topic and begin to prepare for your  Thesis Proposal Examination . The Thesis Proposal Examination should be taken 1-2 years after passing the Preliminary Oral Examination and is a presentation pertaining to research directly related to your thesis proposal. This examination will test the full range of your expertise regarding your thesis topic in order to evaluate your preparation for thesis research and the suitability of your thesis research plan.

Once you pass the Thesis Proposal Examination, you will be in the full swing of research. During this stage, you will synthesize all of the skills you have learned up to this point and use them to distill the material that will become the core of your doctoral thesis. Your days and nights will be filled with intense thesis preparation and research into your thesis topic and finally you will produce a complete thesis dissertation document which you will defend orally during your  Final Oral Examination and Thesis Defense .  The successful completion of these activities yields your Doctor of Philosophy (Ph.D.) in Computer Science!

Throughout your career as a doctoral student you will receive support from your Academic Advisor(s), peer and research groups, and the departmental program administrator as well as a number of individuals across campus who work to best facilitate your progress through your degree program. Our primary goal is to make sure that your experience is positive, productive, and prepares you for a successful career beyond the University of Minnesota. The entirety of the Ph.D. process is complex and at times, rife with academic and administrative requirements. If you have questions regarding your individual degree plan, please do not hesitate to reach out to your advisor, the Director of Graduate Studies or the Graduate Program Coordinator for help.

A total of 55 credits are required to complete the Ph.D. in Computer Science. This includes 31 coursework credits and 24 thesis credits with a GPA of 3.45 or higher.

Coursework credits

Each student must complete 31 credits of graduate coursework, including:

• 16 graduate credits from 5xxx or 8xxx courses with a CSCI designator (with a grade of C- or better)
• 15 credits of  breadth courses  (5 courses), at least one from each category.
• 1 credit of CSCI colloquium (CSCI 8970)
• 6 credits of supporting program coursework or 12 credits from a minor program
• CSCI 8001/8002 unless advised otherwise by research advisor (Introduction to Research in Computer Science I and II)
• Other graduate-level credits to reach a total of at least 31 credits which may include related field courses from programs other than CSCI or courses for a graduate minor

Students have eight calendar years to complete their degree per University requirements.

Transfer credits from a previously acquired M.S. degree may apply to your Ph.D. program. Please speak with the Graduate Program Coordinator for information on transfer credit.

Breadth  coursework consists of five (5) courses (typically 15 credits) taken within three (3) subject areas. The breadth requirement exists to help expose the student to diverse computer science research topics and methods. There is 3.45 GPA minimum requirement for this coursework.

Supporting program courses

Supporting program courses are defined as a minimum of six (6) credits from a supporting program outside of the computer science department. These six credits can be a part of the 12 credits counted towards a minor. A minor is optional for the Ph.D. in Computer Science.

Background knowledge

Background knowledge  courses cover concepts that are integral to a minimal core body of knowledge that all computer science Ph.D. students are expected to posses. These concepts are required prerequisites and all students in the Ph.D. program are required to fulfill these background requirements.

In addition to coursework credits, a minimum of 24 thesis credits are required in order to complete the Ph.D. program. These courses may only be taken following the completion of the WPE/OPE and admission of a student to Ph.D. candidacy.

It is the recommendation of the department that you maximize the thesis credits you take each semester and it is our hope that you will complete the thesis credits in two (2) semesters. Most students will be able to take half in one semester and the other half the next semester. If you still have some classes to take, you can register for the class(es) and then register thesis credits for the rest of the credits, up to the maximum allowed each semester of 14 credits total

When you have completed all of your thesis credits, you will be put in a reduced fringe classification, which allows you to only register for one credit, CSCI 8444 which is designated as the Ph.D. full-time equivalent credit. This credit gives you full-time status for your visa requirements for international students and also full-time status if you hold a graduate assistantship. Your assistantship will only pay for one credit, so if you take any additional credits after you have completed all of your thesis credits, the tuition for those credits will be your responsibility.

For international students who wish to do CPT during the summer and to register for CPT in the fall, you should not register for CSCI 8444 but instead request a reduced course  load  and submit to ISSS. For those who hold an assistantship, you must also submit a  Special Graduate Assistant Registration Tuition Benefits Status Request  form. This form must be submitted before the semester begins and is to be signed by your advisor, your employer (your advisor if an RA, by the DGS if TA) and then by the DGS. It should be submitted to the office and we will make sure it has the DGS signature and then fax it to the Grad Assistant Office. If you have any questions about the distribution of course and thesis credits over your career, please be sure to discuss with the Graduate Program Coordinator.

• Students who take six (6) credits or more are considered full-time graduate students.  All international students and students who hold a graduate assistantship, fellowship, or traineeship are required to be full-time students .
• Almost all of the graduate level courses in computer science (5000 level and above) are 3 credits each.
• Special topics courses (CSCI 5980 or 8980) are courses taught one time only and are good options if the topic is of interest to you. However, please note that these do not count towards breadth requirements.
• All computer science courses must be taken A/F (unless only offered S/N, such as colloquium or plan B project), and no more than one-third of the courses that will count towards your degree can be taken on the S/N basis.
• Students must maintain a minimum GPA of 3.45 for courses counting towards your degree and no courses with a grade below a C- can be included.
• Students in the Doctoral program can use a maximum six (6) credits of directed research or independent study for elective credits. This is defined as CSCI 5991/5994/8991/8994

All requirements for the doctoral degree must be completed and the degree awarded within  five calendar years after passing the preliminary oral examination . Graduate School policy dictates a departmental  annual review  of Ph.D. progress for all students. Each fall, computer science Ph.D. students will be required to complete an annual review form. This form is used by the student’s research advisor to note student progress through the program. All forms are reviewed by the Director of Graduate Studies for satisfactory progress. Progress Guidelines are available in Appendix A of the Graduate Student Handbook.

The Graduate Program Coordinator can answer most questions and advise students on degree requirements, department procedures, or general issues about being a graduate student. All new students are expected to meet with her upon arrival as well as several times throughout your graduate career in order to best facilitate your program.

The Director of Graduate Studies is the official advisor of record for all students, unless an advisor was assigned at the time of admission. Only  faculty with graduate education responsibilities  are eligible to serve as advisors for graduate students. The advisor-advisee relationship is a mutual and an advisor must agree to advise any student. Once a student determines his or her advisor they will fill out a  Declaration of Advisor  form. A student may change advisors at any time using the same form. Please note that the new and the previous advisor must sign to acknowledge this change.

Most Ph.D. students have been assigned advisors in their field of interest at the time of entry into the university. Students are encouraged to talk to their assigned advisor as well as other faculty members in their interest area to determine if their assigned advisor is best suited to their research goals. It is not uncommon to discover that your permanent research advisor is different from your pre-assigned one. You are expected to take some time to look around, talk with professors and other graduate students, and then talk with your prospective advisor.  We expect you to find an advisor by the end of your first year in the program.  Advising is a mutually voluntary arrangement. You never will be obligated to work with someone against your choice, and no faculty member is obligated to take on any particular student.

For questions regarding the advising process please contact the  Director of Graduate Studies .

Stephen Guy

Associate Professor, Director of Graduate Studies

5-225F Keller Hall 612-625-3368 [email protected]

Joseph Nieszner

Senior Graduate Program Coordinator

330G Lind Hall [email protected]   [email protected]

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Computer Science (4 Year Programme) MPhil/PhD

London, Bloomsbury

The PhD programme in UCL Computer Science is a 4-year programme, in which you will work within research groups on important and challenging problems in the development of computer science. We have research groups that cover many of the leading-edge topics in computer science , and you will be supervised by academics at the very forefront of their field.

UK tuition fees (2024/25)

Overseas tuition fees (2024/25), programme starts, applications accepted.

• Entry requirements

A UK Master's degree in a relevant discipline with Merit, or a minimum of an upper second-class UK Bachelor's degree in a relevant discipline, or an overseas qualification of an equivalent standard. Work experience may also be taken into account.

The English language level for this programme is: Level 1

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

If you are intending to apply for a time-limited visa to complete your UCL studies (e.g., Student visa, Skilled worker visa, PBS dependant visa etc.) you may be required to obtain ATAS clearance . This will be confirmed to you if you obtain an offer of a place. Please note that ATAS processing times can take up to six months, so we recommend you consider these timelines when submitting your application to UCL.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website .

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

On this PhD programme, you will work within research groups on challenging computer science projects.

Our research groups cover leading-edge topics , and our academics are at the forefront of their field.

The research groups, the department , and the college, provide numerous opportunities to learn more about your field and the skills required to develop your research and future careers.

Who this course is for

This programme is best suited for people wishing to embark on an academic career, as well as those interested in finding work in industry. You will be assigned a first and second supervisor, who will guide you in the development of your research project and your abilities as a researcher. The research groups, the department, and the college, provide numerous opportunities for you to learn more about your field (e.g. seminars, conferences, and journal clubs) and the skills required for you to develop your research and future careers (e.g. training courses). Many of our students have had their research results published and recognised at leading international conferences during their time on the PhD programme.

What this course will give you

UCL is ranked 9th globally in the latest QS World University Rankings (2024), giving you an exciting opportunity to study at one of the world's best universities.

UCL Computer Science is recognised as a world leader in teaching and research. The department was ranked first in England and second in the UK for research power in Computer Science and Informatics in the most recent Research Excellence Framework ( REF2021 ). You will learn from leading experts with an outstanding reputation in the field. 

Code written at UCL is used across all 3G mobile networks for instant messaging and videoconferencing; medical image computing has led to faster prostate cancer diagnosis and has developed tools to help neurosurgeons avoid damaging essential communication pathways during brain surgery; and our human-centred approach to computer security has transformed the UK government's delivery of online security.

This MPhil/PhD in Computer Science is a research degree programme that will not only challenge and stimulate you, but also has the potential to lead to a varied and interesting career and introduce you to valuable contacts in academia and the industry.

The foundation of your career

Your employability will be greatly enhanced by working alongside world-leading researchers in cutting-edge research areas such as virtual environments, networked systems, human-computer interaction and financial computing. UCL's approach is multi-disciplinary and UCL Computer Science shares ideas and resources from across all departments of Faculty of Engineering Sciences and beyond. Our alumni have a successful record of finding work, or have founded their own successful start-up companies, because they have an excellent understanding of the current questions which face industry and have the skills and the experience to market innovative solutions.

Employability

UCL Computer Science graduates secure careers in a variety of organisations, including global IT consultancies, City banks and specialist companies in manufacturing industries.

The department takes pride in helping students in their career choices and offers placements and internships with numerous start-up technology companies, including those on Silicon Roundabout, world-leading companies such as Google, Skype and Facebook, and multi national finance companies, including Morgan Stanley, Deutsche Bank and JP Morgan.

Our graduates secure roles such as applications developers, information systems managers, IT consultants, multimedia programmers, software engineers and systems analysts in companies such as Microsoft, Cisco, Bloomberg, PwC and IBM.

UCL Computer Science is located in the heart of London and subsequently has strong links with industry. You will have regular opportunities to undertake internships at world-leading research organisations. We frequently welcome industry executives to observe your project presentations, and we host networking events with technology entrepreneurs.

You will also benefit from a location close to the City of London and Canary Wharf to work on projects with leading global financial companies. London is also home to numerous technology communities, for example the Graduate Developer Community, who meet regularly and provide mentors for students interested in finding developer roles when they graduate.

Teaching and learning

You are assigned a first and second supervisor who you will meet regularly. You are also assigned a research group who normally meet regularly for research seminars and related activities in the department.

You will participate in three vivas during the course of your study. These are useful feedback opportunities and allow you to demonstrate your understanding of the literature, your progress in your research and eventually, your final thesis and research. For each viva, you will be expected to produce a detailed report of your work to date and to attend a 'verbal exam' with supervisors and/or external academics/experts.

During your research degree, you will have regular meetings with your primary supervisor, in addition to contact with your secondary supervisor and participation in group meetings. Full-time study should comprise of 40 hours per week .

Research areas and structure

• Bioinformatics: protein structure; genome analysis; transmembrane protein modelling; de novo protein design methods; exploiting grid technology; mathematical modelling of biological processes
• Financial computing: software engineering; computational statistics and machine learning; mathematical modelling
• Human centred systems: usability of security and multimedia systems; making sense of information; human error and cognitive resilience
• Information security: human and organisational aspects of security; privacy-enhancing technologies; cryptography and cryptocurrencies; cybersecurity in public policy and international relations; systems security and cybercrime
• Intelligent systems: knowledge representation and reasoning; machine learning
• Media futures: digital rights management; information retrieval; computational social science; recommender systems
• Networks: internet architecture; protocols; mobile networked systems; applications and evolution; high-speed networking
• Programming Principles, Verification and Logic’: logic and the semantics of programs; automated tools for verification and program analysis; produce mathematically rigorous concepts and techniques that aid in the construction and analysis of computer systems; applied logic outreach in AI, security, biology, economics
• Software systems engineering: requirements engineering; software architecture; middleware technologies; distributed systems; software tools and environments; mobile computing
• Virtual environments: presence, virtual characters; interaction; rendering; mixed reality
• Vision and imaging science: face recognition; medical image analysis; statistical modelling of colour information; inverse problems and building mathematical models for augmented reality; diffusion tensor imaging

Research environment

UCL Computer Science is one of the leading university centres for computer science research in Europe. The department is very well-connected with research groups across the university, and is involved in many exciting multi-disciplinary research projects.

Furthermore, research groups in the department are heavily involved in collaborative research and development projects with other universities and with companies in the UK and internationally. UCL provides significant support for technology transfer, and in particular for technology start-ups, and the department has an increasingly successful record of spin-out companies including a number of spin-outs that have been acquired by Google, Facebook, Amazon, etc.

Month 0 Registration - initially MPhil registration.

Month 0-6 - General reading, directed by the supervisor, in the area of interest. This should bring you up to the sharp end of the area and allow you to appreciate what the research problems are.

Months 6-9 - More detailed reading, aimed at becoming expert enough to tackle a thesis project. A small focused project is in order here to pin the reading on. A report on the year's activities should begin to be prepared.

Month 9 - FORMAL 1ST-YEAR VIVA (10-12 for Part-time) This is the first major examination, and must take place no more than 9 months from the start date. A feedback activity. Given a read of your report, the supervisor, 2nd supervisor and an 'assessor' review the work done with the aim of providing you with proper feedback on your work. This is also a good opportunity to get feedback for the Transfer Viva and is often used as a “mock transfer”.

Months 12-18 - FORMAL TRANSFER VIVA (15-21 for Part-time) Also known as the “Upgrade Viva” - this is where you would upgrade your expected qualification from MPhil to PhD. A substantial project report is expected demonstrating the ability to conduct research, with initial research results, and a plan for completion of the work and writing of the thesis. The outcome of the viva will determine whether you are allowed to transfer registration from MPhil to PhD.

Months 24-36 - Thesis project work being tidied up and turned into a unified piece of work. Thesis writing being planned and chapters being drafted. You are now eligible for Completing Research Status

Month 36 - MOCK VIVA (48-60 for Part-time) A draft thesis and mock viva. This is to be attended by the supervisor, second supervisor and assessor and any others thought relevant. Thesis submission forms (aka Entry forms) completed and submitted.

Months 36-42 - Complete the writing of the thesis.

Month 42 - (60-72 for Part-time) Submit thesis.

See full-time summary

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk . Further information can also be obtained from the UCL Student Support and Wellbeing team .

Fees and funding

Fees for this course.

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees .

Additional costs

As each research project is unique in nature, the AFE (Additional Fee Element) is calculated on a student-by-student basis and is determined by your academic supervisor. Please contact your supervisor for further details.

A student conference and travel fund is available to students within the department to help with costs associated with attending and presenting at conferences. Applications are considered on a case-by-case basis.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs .

Funding your studies

UCL offers various funding opportunities for postgraduate students. Please see UCL's Scholarships website for more information.

The department offers funding for overseas and UK students. Please see the Computer Science website for more information.

Home students will have the opportunity to apply for EPSRC DTP Studentships where available.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website .

CSC-UCL Joint Research Scholarship

Value: Fees, maintenance and travel (Duration of programme) Criteria Based on academic merit Eligibility: EU, Overseas

Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit to see if you need to consider these in your application preparation. All applicants are asked to identify and contact potential supervisors before making an application. For more information see our How to apply page.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

Got questions get in touch.

Computer Science

[email protected]

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Doctoral Program

The primary focus of the doctoral program is research, with the philosophy that students learn best by doing—beginning as apprentices and becoming junior colleagues working with faculty on scholarly research projects. The faculty in the department conduct research in all areas of computer science. The doctoral degree requires a dissertation based on the candidate’s original research, which is supervised by a faculty member, and all students in the doctioral program are actively engaged in research throughout the program.

The PhD is the Computer Science Department’s primary doctoral program.  PhD students are expected to be full-time on-campus during every fall and spring academic semester from initial enrollment until the dissertation has been distributed to their defense committee, except during leaves of absence approved by the university.  PhD students spend at least half of their time on research under the direction of their faculty adviser from their first day in the program and devote themselves full time to research after coursework and other preliminaries have been completed. PhD students are also expected to participate in departmental and laboratory activities full time throughout the program, except possibly for summer internships elsewhere, and the department does not consider admission of part-time PhD students. The policy on outside activities by PhD students is here .

DEPARTMENTAL INFORMATION FOR DOCTORAL STUDENTS

• Program Requirements
• MS leading to PhD
• Milestones Chart
• Milestones Registration Form: Candidacy, Thesis Proposal, Thesis Defense
• Doctoral Course Import Forms
• Doctoral Algorithms Prerequisite Form
• Data Science Specialization Option  (further details here )

SCHOOL/UNIVERSITY INFORMATION FOR DOCTORAL STUDENTS

• Registration
• SEAS Doctoral Fieldwork (CPT) Policy
• Time-Off Policy for Doctoral Students on Appointment in the Sciences and Related Research Fields

GENERAL DOCTORAL INFORMATION AND ADVICE

• CAREER Club
• Computer Science Open Data
• Computer Science Graduate Job and Interview Guide
• Background in case you ever need to teach online with two days notice
• The Definitive ‘what do I ask/look for’ in a PhD Advisor Guide
• The Thesis Whisperer
• Prem Devanbu’s Review Anti-Patterns
• Computer Science Rankings
• Michael Ernst’s Compilation of Great Advice
• Productivity Tips for PhD Students
• Getting Admitted to a Top PhD Program
• Tips on the Interview Process
• Networking on the network
• Advice on research and writing
• More advice on writing
• Corporate Lab or Academic Department, Which Fits?
• How To Survive A Thesis Defense
• 10 easy ways to fail a PhD
• Dealing with plagiarism
• Academic job site
• Computing Research Association
• IEEE Computer Society

(link suggestions appreciated; send email to [email protected] )

Last updated on June 5, 2024.

Find open faculty positions here .

Computer Science at Columbia University

Upcoming events, in the news, press mentions, dean boyce's statement on amicus brief filed by president bollinger.

President Bollinger announced that Columbia University along with many other academic institutions (sixteen, including all Ivy League universities) filed an amicus brief in the U.S. District Court for the Eastern District of New York challenging the Executive Order regarding immigrants from seven designated countries and refugees. Among other things, the brief asserts that “safety and security concerns can be addressed in a manner that is consistent with the values America has always stood for, including the free flow of ideas and people across borders and the welcoming of immigrants to our universities.”

This recent action provides a moment for us to collectively reflect on our community within Columbia Engineering and the importance of our commitment to maintaining an open and welcoming community for all students, faculty, researchers and administrative staff. As a School of Engineering and Applied Science, we are fortunate to attract students and faculty from diverse backgrounds, from across the country, and from around the world. It is a great benefit to be able to gather engineers and scientists of so many different perspectives and talents – all with a commitment to learning, a focus on pushing the frontiers of knowledge and discovery, and with a passion for translating our work to impact humanity.

I am proud of our community, and wish to take this opportunity to reinforce our collective commitment to maintaining an open and collegial environment. We are fortunate to have the privilege to learn from one another, and to study, work, and live together in such a dynamic and vibrant place as Columbia.

Mary C. Boyce Dean of Engineering Morris A. and Alma Schapiro Professor

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PhD in Computer Science

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The PhD is the primary research degree that can be taken in the Department of Computer Science and Technology. The Cambridge PhD is a three to four-year full-time (five to seven-year part-time) programme of individual research on a topic agreed by the student and the Department, under the guidance of a staff member as the student's supervisor. 

All research students are admitted to read for the PhD degree on a probationary basis and will be registered for the Certificate of Postgraduate Study (CPGS) in the first instance. During this year students may do some additional coursework and will write a research report that is likely to form the foundation of the eventual PhD thesis. The CPGS will involve four components:

Research skills training

Practical work

Research report of no more than 10,000 words

Attendance at a research workshops and research seminars

At the end of the third term and on completion of the CPGS, students whose performance indicates that they would be able to complete a PhD in a reasonable time will be upgraded to PhD status. A student who is not upgraded to PhD status, and who has completed three terms of study, will normally be awarded the CPGS alone. They will not submit a thesis for the PhD degree.

There is an expectation that all research students will contribute to teaching in the department for which some training will be provided. Research students will submit a log - or tally-sheet - of teaching activities annually at the end of June. 

Students are expected to complete the substance of their research by the end of their third year, submitting their thesis then or within a few months.

Applicants wishing to apply to undertake a PhD on a part-time basis should refer to the Department's admissions advice for potential part-time students.

The Postgraduate Virtual Open Day usually takes place at the end of October. It’s a great opportunity to ask questions to admissions staff and academics, explore the Colleges virtually, and to find out more about courses, the application process and funding opportunities. Visit the  Postgraduate Open Day  page for more details.

See further the  Postgraduate Admissions Events  pages for other events relating to Postgraduate study, including study fairs, visits and international events.

Key Information

3-4 years full-time, 4-7 years part-time, study mode : research, doctor of philosophy, department of computer science and technology, course - related enquiries, application - related enquiries, course on department website, dates and deadlines:, lent 2024 (closed).

Some courses can close early. See the Deadlines page for guidance on when to apply.

Michaelmas 2024 (Closed)

Funding deadlines.

These deadlines apply to applications for courses starting in Michaelmas 2024, Lent 2025 and Easter 2025.

Similar Courses

• Advanced Computer Science MPhil
• Machine Learning and Machine Intelligence MPhil
• Linguistics: Theoretical and Applied Linguistics PhD
• Biological Science (EBI) PhD
• Medical Science (Oncology) MPhil

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Ph.D. Program

The Allen School provides every student accepted to our Ph.D. program with full financial support in the form of teaching and research assistantships or fellowships, from program inception to degree. Students earn an integrated Master’s Degree on their path to the Ph.D. Key features of our program include:

• Comprehensive, high-quality graduate computer science curriculum.
• A vibrant academic and social community.
• Welcoming and inclusive environment for international students, women, and other underrepresented groups.
• Robust schedule of colloquia and lectures on current topics in research and technology.
• Leading-edge interdisciplinary research opportunities, on and off campus.

Our students benefit from many collaborations and relationships that we have developed across the campus and in the region. In addition to being the headquarters of established technology leaders such as Microsoft and Amazon, Seattle is also home to an extensive (and ever-growing) list of engineering centers established by major industry players from outside the Pacific Northwest.

Admission to the Allen School’s Ph.D. program is competitive. Each year, we receive applications from approximately 2,500 prospective graduate students from around the globe for 50 - 60 positions. We accept applications once a year, for entrance in the following autumn quarter. Our application process opens on September 1, and all application materials are due December 15, or the next following business day, if the 15th falls on a weekend. The Allen School hosts its annual Grad Visit Days in March for applicants who have received an offer of admission. This event provides an opportunity for applicants to meet with faculty, get to know their prospective colleagues, and experience the Seattle area’s quality of life.

The Ph.D. Process

The Allen School's Ph.D. process consists of three components: coursework, research, and thesis preparation. At the beginning of the program, students will take graduate-level courses in an array of topics spanning theory, systems, programming, and applications. They will also develop and refine their research skills working with their faculty advisor and other collaborators. These skills include information analysis and synthesis as well as written and verbal presentation capabilities. Student progress is measured at multiple steps throughout the program: the Qualifying Evaluation (a.k.a. “quals”), the General Exam, and the Candidacy of Philosophy, leading to the preparation and defense of their dissertation to obtain their Doctor of Philosophy degree.

Course Guide

Students are required to complete approximately 90 credits on their way to obtaining a Ph.D. degree in Computer Science & Engineering from the Allen School, 60 of which must be earned at the University of Washington. Explore our online course guide to peruse available courses, teaching schedules, internship credit, and specialized degree tracks available to Ph.D. students.

Student Handbook

Visit our online student handbook for essential information and advice about being a Ph.D. student in the Allen School, from available fellowships and travel grants, to navigating the annual review of progress, to mentoring undergraduate researchers. This section also contains practical information such as allocation of office space and obtaining health insurance, as well as the forms students will need to complete at various points throughout the program.

The Allen School's graduate advising team is here to guide prospective and current students as they navigate the application and registration process and help tailor the Allen School experience to their education and career goals.

Computer Science, PhD

Whiting school of engineering.

The goal of the Doctor of Philosophy (Ph.D.) program in the Department of Computer Science is to prepare first-rate scholars in computer science. Successful graduates may assume significant positions in academia, research institutes, industry, or government laboratories.

Applications for admission to the Ph.D. program in Computer Science are reviewed by a faculty committee. Although specific criteria isn’t rigid, all students admitted must exhibit exceptional intellectual achievements and promise. Applicants must submit letters of recommendation, and (for international applicants) TOEFL/IELTS scores. Visit departmental admissions page  for more information on the application process.

For details regarding CS Ph.D. program requirements and policies, please visit the Advising Manual on our departmental website.

Financial Aid

All full-time, residential PhD students are admitted with full financial support regardless of citizenship or national origin.  This includes an annual stipend, full tuition, matriculation fee, medical and dental insurance, and paid health insurance premiums for eligible dependent children and spouses unable to work in the US, including dental and vision.  More details and eligibility information will be detailed in admissions letters.

Program Requirements

University residency.

Two consecutive semesters of residence as a full-time graduate student are required.

Seminar Attendance

All Ph.D. degree candidates are required to maintain satisfactory attendance in the Computer Science Seminar each semester for the duration of their enrollment in the program.  Although seminar attendance is required, the seminar may not be counted toward the qualifying course requirement. Enrollment in  EN.601.801 Computer Science Seminar  is required for first and second year students only.

Responsible Conduct of Research and Academic Ethics

All doctoral students are required to take AS.360.625 Responsible Conduct of Research . Students are expected to complete the course by the end of their first year. Failure to do so may result in a loss of funding. Additional information regarding this requirement can be found on the WSE research webpage . In addition, all doctoral students must complete the course EN.500.603 Graduate Academic Ethics .

Qualifying Course Requirements

The Department of Computer Science classifies its courses into five core distribution areas: Applications, Reasoning, Software, Systems and Theory.  Ph.D. candidates must complete eight courses total (3 class hours/credits each), and at least five of those eight courses must be taught in the Department of Computer Science.  Of those courses, four out of the five core distribution areas must be satisfied.  A current  listing of courses with area designators  is provided on the departmental website. The areas are also encoded as POS (program of study) tags in SIS. Ph.D. students may complete remaining elective graduate courses (chosen from any CS area or from closely related departments such as Electrical and Computer Engineering, Cognitive Science, Mathematics, or Applied Mathematics and Statistics) for a total of eight courses. Computer Science graduate students may count 600-level and above graduate courses. The coursework program must be approved by the student’s faculty advisor. The overall grade point average for these eight courses must be at least equivalent to a B+. No course with a grade of less than C- may be counted toward this Ph.D. qualifying course requirement. Other than independent study courses, no courses with grades of P or S can be counted toward the coursework requirement. Courses with grades of P or S will not be included in the grade point average calculation. One of the courses required for the degree, but only one, may be replaced by 3 credits from comparable short courses. With approval of the student’s faculty advisor, up to two courses can be transferred from graduate programs of other institutions; more than two such courses can be transferred with approval of the department. It is the obligation of the student to provide all necessary documentation to the Department of Computer Science regarding the course(s) for which transfer credit is being requested. Students are expected to complete the course requirements by the end of their second year as a Ph.D. candidate. 

Qualifying Project Requirements

A Ph.D. student must complete two projects, each under the supervision and written agreement of a different faculty member. One project must be under the supervision of a faculty member with an appointment in the Department of Computer Science (Professor, Research Professor, Visiting or Joint appointment). The second project can be supervised by a different tenure-track or research faculty member in any division of Johns Hopkins, or with advance approval from the department, by any outside researcher.  Upon conclusion of each project, the student must write a “Project Report” describing the project in detail. This report will be a public document and will be kept on file in the department office. The supervising faculty member must approve the project report. Students are expected to complete the qualifying projects by the end of their third year as a Ph.D. candidate. 

Upon completion of the Ph.D. qualifying course requirements and the first qualifying project, students are ordinarily eligible to receive a master of science in engineering degree. The degree will be awarded upon student request.

Graduate Board Oral Examination (GBO)

This examination is a university requirement, ideally taken in the student's third year. The oral exam is administered by a committee consisting 5 members.  Students must select two members from inside the department and two members from outside the department, plus a 5th member who is either inside or outside the department.  The exam seeks to establish the student’s readiness to conduct original research in the area of their “Preliminary Research Proposal,” which should be distributed to the examiners in advance and presented by the student at the start of the exam.

Part-Time Ph.D.

Two consecutive semesters of residence as a full-time graduate student are required by the university. Attempting to obtain a Ph.D. is a major commitment and involves close coordination with a faculty advisor in the department. Part-time students must be able to establish and maintain these close links, therefore part-time study is by advanced and special permission only.

Departmental Seminar

Ph.D. students must give an official departmental seminar on their research area. This is to be done after the GBO and prior to the dissertation defense, or as part of the dissertation defense.

Dissertation and Defense

Ph.D. students must write a dissertation consisting of original research in their chosen area. They must deliver a public presentation of the dissertation before a dissertation committee consisting of the faculty advisor, a second faculty member in the Department of Computer Science (who must have a primary tenure-track appointment in the Department if the advisor does not), and one or more other members with Ph.D. degrees. In conformity with University requirements, the members of the dissertation committee must submit a referee’s letter to the Graduate Board recommending that the dissertation be accepted. Completed dissertations will be formatted and submitted to the Milton S. Eisenhower Library for electronic publication .

Teaching Requirement

All Ph.D. students are required to serve as a Teaching Assistant at least one semester during their program of study. As part of the requirement, the supervising course instructor must give the TA an opportunity to be in front of a group of students at least once during the course. Students are required to sign-up for the course EN.601.807 Teaching Practicum  during the semester in which the requirement is being fulfilled, and at the end of the semester their performance will be evaluated by the course instructor.

Student Progress Review

Ph.D. students are reviewed annually by their advisor(s) and the department, and notified in writing as to their standing in the program. Students deemed to not be making satisfactory progress may be placed on probation.

Alternatively, use our A–Z index

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PhD Computer Science / Overview

Year of entry: 2024

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The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent).

Other combinations of qualifications and research or work experience may also be considered. Please contact the admissions team to check.

Full entry requirements

Apply online

In your application you’ll need to include:

• The name of this programme
• Your research project title (i.e. the advertised project name or proposed project name) or area of research
• Your proposed supervisor’s name
• If you already have funding or you wish to be considered for any of the available funding
• A supporting statement (see 'Advice to Applicants' for what to include)
• Details of your previous university level study
• Names and contact details of your two referees.

Find out how this programme aligns to the UN Sustainable Development Goals , including learning which relates to:

Goal 4: Quality education

Goal 8: decent work and economic growth, goal 9: industry, innovation and infrastructure, goal 17: partnerships for the goals, programme options.

Programme description

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The PhD is a three-year (or six year, if taken part-time) degree resulting in a substantial thesis.

The Department of Computer Science is one of the largest in the UK covering a huge spectrum of Computer Science topics. We currently have research groups ranging from Advanced Processor Technologies to Text Mining.

Our core Computer Science research is augmented by interdisciplinary research taking place at the interface with discipline areas including mathematics, physics, medicine and biology.

A detailed overview of the Department's research groups and core and interdisciplinary research themes is available in the 'research' area of our website and you can identify a possible project from our list of available projects .

For entry in the academic year beginning September 2024, the tuition fees are as follows:

• PhD (full-time) UK students (per annum): Band A £4,786; Band B £7,000; Band C £10,000; Band D £14,500; Band E £24,500 International, including EU, students (per annum): Band A £28,000; Band B £30,000; Band C £35,500; Band D £43,000; Band E £57,000
• PhD (part-time) UK students (per annum): Band A £2393; Band B £3,500; Band C £5,000; Band D £7,250; Band E 12,250 International, including EU, students (per annum): Band A £14,000; Band B £15,000; Band C £17,750; Band D £21,500; Band E £28,500

Further information for EU students can be found on our dedicated EU page.

The programme fee will vary depending on the cost of running the project. Fees quoted are fully inclusive and, therefore, you will not be required to pay any additional bench fees or administration costs.

All fees for entry will be subject to yearly review and incremental rises per annum are also likely over the duration of the course for Home students (fees are typically fixed for International students, for the course duration at the year of entry). For general fees information please visit the postgraduate fees page .

Always contact the Admissions team if you are unsure which fees apply to your project.

Scholarships/sponsorships

There are a range of scholarships, studentships and awards at university, faculty and department level to support both UK and overseas postgraduate researchers.

To be considered for many of our scholarships, you’ll need to be nominated by your proposed supervisor. Therefore, we’d highly recommend you discuss potential sources of funding with your supervisor first, so they can advise on your suitability and make sure you meet nomination deadlines.

For more information about our scholarships, visit our funding page or use our funding database to search for scholarships, studentships and awards you may be eligible for.

UN Sustainable Development Goals

The 17 United Nations Sustainable Development Goals (SDGs) are the world's call to action on the most pressing challenges facing humanity. At The University of Manchester, we address the SDGs through our research and particularly in partnership with our students.

Led by our innovative research, our teaching ensures that all our graduates are empowered, inspired and equipped to address the key socio-political and environmental challenges facing the world.

To illustrate how our teaching will empower you as a change maker, we've highlighted the key SDGs that our programmes address.

Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all

Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all

Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation

Strengthen the means of implementation and revitalize the Global Partnership for Sustainable Development

Contact details

The School of Engineering creates a world of possibilities for students pursuing skills and understanding. Through dynamic research and teaching we develop engineering solutions that make a difference to society in an ethical and sustainable way.  Science-based engineering is at the heart of what we do, and through collaboration we support the engineers and scientists of tomorrow to become technically strong, analytically innovative and creative. Find out more about Science and Engineering at Manchester .

Programmes in related subject areas

Use the links below to view lists of programmes in related subject areas.

• Computer Science
• Informatics

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The University of Manchester is regulated by the Office for Students (OfS). The OfS aims to help students succeed in Higher Education by ensuring they receive excellent information and guidance, get high quality education that prepares them for the future and by protecting their interests. More information can be found at the OfS website .

You can find regulations and policies relating to student life at The University of Manchester, including our Degree Regulations and Complaints Procedure, on our regulations website .

PhD Time Limits & Milestones

Graduate college time requirements for degree.

• Bachelors to PhD Program Time Limits - 7 years from first term enrolled in doctoral program. Please see Illinois CS PhD Milestones below for the Department's Time Requirement for Ph.D.
• PhD Program Time Limits with a MS at Illinois - 5 years (2 yrs. for MS and 5 yrs. for PhD)
• PhD Program Time Limits with a Non-Illinois MS - 6 years from first term enrolled in doctoral program

Illinois CS PhD Milestone Timeline

The department's timeline is an average of 6 years to complete the Ph.D. degree. The timeline below is based on a 5-year program of study.

Graduate Advising

The Graduate Academic Office, a guiding hand for graduate students, offers assistance every weekday.

   Search  9388 Lightwave Ave, San Diego, CA 92123 Modal window with site-search and helpful links By submitting your information to National University as my electronic signature and submitting this form by clicking the Request Info button above, I provide my express written consent to representatives of National University and National University affiliates (including City University of Seattle) to contact me about educational opportunities. This includes the use of automated technology, such as an automatic dialing system and pre-recorded or artificial voice messages, text messages, and mail, both electronic and physical, to the phone numbers (including cellular) and e-mail address(es) I have provided. I confirm that the information provided on this form is accurate and complete. I also understand that certain degree programs may not be available in all states. Message and data rates may apply. Message frequency may vary. I understand that consent is not a condition to purchase any goods, services or property, and that I may at any time by sending an email to . I understand that if I am submitting my personal data from outside of the United States, I am consenting to the transfer of my personal data to, and its storage in, the United States, and I understand that my personal data will be subject to processing in accordance with U.S. laws, unless stated otherwise in our . Please review our privacy policy for more details or contact us at . By submitting my information, I acknowledge that I have read and reviewed the .  By submitting my information, I acknowledge that I have read and reviewed the Student Code of Conduct located in the . National University Chat Options --> --> --> --> --> --> --> --> -->
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	Jul 02, 2024   National University Volume 86C-2 Catalog - July 2024     National University Volume 86C-2 Catalog - July 2024 Doctor of Philosophy in Computer Science Description of program. The Doctor of Philosophy in Computer Science (PhD-CS) program takes an applied approach to computer science theory and research. Students will get hands on experience, explore advanced topics, learn the very latest concepts, and have the opportunity to propose their own research. They will also be able to build a portfolio of work while completing their doctoral studies. Click here for potential career opportunities within the PhD-CS. Learning Outcomes Develop knowledge in computer science based on a synthesis of current theories Explain theories, applications, and perspectives related to computer science Evaluate theories of ethics and risk management in computers and emerging technologies Formulate strategies for managing computing resources in global organizations Contribute to the body of theory and practice in computer science Basis for Admissions Admission to the PhD in Computer Science program requires a master’s degree from a regionally accredited or nationally accredited academic institution. Degree Requirements The University may accept a maximum of 12 semester credit hours in transfer toward the doctoral degree for graduate coursework completed at an accredited college or university with a grade of “B” or better. The PhD-CS degree program also has the following graduation requirements: A minimum of 48 credit hours of graduate instructions must be completed through the University GPA of 3.0 (letter grade of “B”) or higher Submission of approved final dissertation manuscript to the University Registrar, including the original unbound manuscript and an electronic copy Official transcripts on file for all transfer credit hours accepted by the University All financial obligations must be met before the student will be issued their complimentary diploma Fundamental Competencies All PhD-CS students are required to demonstrate competency in these areas: Computer Competency  - Doctoral students are required to have computer skills necessary for completing a dissertation. Students must be able to prepare documents using advanced word processing skills (e.g., creation of tables and figures, headers and footers, page breaks, tables of contents, hanging indents). Students must use computer programs for the statistical analysis of data (e.g., SAS). Students must produce a computer-based presentation (e.g., PowerPoint) for their dissertation oral examination. Dissertation Completion Pathway The University’s mission is dedicated to assisting students in achieving their academic aspirations and helping them become valuable contributors to their community and profession. To support our mission, the University now offers a dissertation completion pathway for students who have successfully completed their doctoral coursework and achieved doctoral candidacy at a previous institution but were unable to complete their dissertation.  The University’s Dissertation Completion Pathway (DCP) offers a unique opportunity for students to complete their doctorate in one of the doctoral programs offered at the University (excluding the PhD-MFT and DNP). Students successfully meeting the entrance and application requirements will complete a minimum of 23 credit hours to earn their doctorate. Click for more information on the  Dissertation Completion Pathway.   Time to Completion The University allows 7 years to complete all doctoral programs of 60 credits or less. The median time to completion for this program is 49 months. Time to completion varies depending upon the pace in which a student completes courses and the number of transfer credits accepted. As most students are working adults, balancing educational, professional, and personal commitments, our academic and finance advisors will work with you to develop a program schedule that works best for your needs. Students following the preferred schedule designed by the Dean for this program, and applying no transfer credits, can expect to finish in as little as 40 months. Dissertation Process Faculty assists each Doctoral student to reach this high goal through a systematic process leading to a high-quality completed dissertation. A PhD dissertation is a scholarly documentation of research that makes an original contribution to the field of study. This process requires care in choosing a topic, documenting its importance, planning the methodology, and conducting the research. These activities lead smoothly into the writing and oral presentation of the dissertation. A doctoral candidate must be continuously enrolled throughout the series of dissertation courses. Dissertation courses are automatically scheduled and accepted without a break in scheduling to ensure that students remain in continuous enrollment throughout the dissertation course sequence. If additional time is required to complete any of the dissertation courses, students must re-enroll and pay the tuition for that course. Continuous enrollment will only be permitted when students demonstrate progress toward completing dissertation requirements. The Dissertation Committee determines progress. Course Sequence The PhD program requires a minimum of 60 credits. Additional credit hours may be allowed as needed to complete the dissertation research. If granted, additional courses will be added to the student degree program in alignment with the SAP and Academic Maximum Time to Completion policies. Students who do not complete their program in accordance with these policies may be dismissed. **Students select one research methods and one directed research course based on their own research proposal.  TIM-8102 - Principles of Computer Science TIM-8110 - Programming Languages & Algorithms TIM-7011 - Management of Computer Networks TIM-8122 - Distributed Algorithms and Parallel Computing TIM-7020 - Databases & Business Intelligence TIM-8131 - Data Mining TIM-8301 - Principles of Cybersecurity TIM-8340 - Secure Software Development TIM-7101 - Statistics with Technology Applications TIM-8150 - Artificial Intelligence TIM-8140 - Software Engineering TIM-7211 - Introduction to Research Design and Methodology for Technology Leaders   ** -OR-   ** -OR-   **   ** -OR-   ** -OR-    **                                      TIM-8190 - Computer Science Policy and Strategy CMP-9701CS - PhD Pre-Candidacy Prospectus DIS-9901A - Components of the Dissertation DIS-9902A - The Dissertation Proposal DIS-9903A - Institutional Review Board (IRB) and Data Collection DIS-9904A - The Dissertation Manuscript and Defense Study at Cambridge About the university, research at cambridge. Undergraduate courses Events and open days Fees and finance Postgraduate courses How to apply Postgraduate events Fees and funding International students Continuing education Executive and professional education Courses in education How the University and Colleges work Term dates and calendars Visiting the University Annual reports Equality and diversity A global university Public engagement Give to Cambridge For Cambridge students For our researchers Business and enterprise Colleges & departments Email & phone search Museums & collections PhD in Computer Science Department of Computer Science and Technology Sign in with Raven People overview Research staff PhD students Professional services staff Affiliated lecturers Overview of Professional Services Staff Seminars overview Weekly timetable Wednesday seminars Wednesday seminar recordings ➥ Wheeler lectures Computer Laboratory 75th anniversary ➥ women@CL 10th anniversary ➥ Job vacancies ➥ Library resources ➥ How to get here William Gates Building layout Contact information Department calendar ➥ Accelerate Programme for Scientific Discovery overview Data Trusts Initiative overview Pilot Funding FAQs Research Funding FAQs Cambridge Ring overview Ring Events Hall of Fame Hall of Fame Awards Hall of Fame - Nominations The Supporters' Club overview Industrial Collaboration Annual Recruitment Fair overview Graduate Opportunities Summer internships Technical Talks Supporter Events and Competitions How to join Collaborate with Us Cambridge Centre for Carbon Credits (4C) Equality and Diversity overview Athena SWAN E&D Committee Support and Development Targeted funding LGBTQ+@CL overview Links and resources Queer Library women@CL overview About Us overview Friends of women@CL overview Twentieth Anniversary of Women@CL Tech Events Students' experiences Contact overview Mailing lists Scholarships Initiatives Dignity Policy Outreach overview Women in Computer Science Programme Google DeepMind Research Ready programme overview Accommodation and Pay Application Eligibility Raspberry Pi Tutorials ➥ Wiseman prize Research overview Application areas Research themes Algorithms and Complexity Computer Architecture overview Creating a new Computer Architecture Research Centre Graphics, Vision and Imaging Science Human-Centred Computing Machine Learning and Artificial Intelligence Mobile Systems, Robotics and Automation Natural Language Processing Programming Languages, Semantics and Verification Systems and Networking Research groups overview Computer Architecture Group overview Student projects Energy and Environment Group overview Declaration Publications EEG Research Group Past seminars Learning and Human Intelligence Group overview Quantum Computing Group Technical Reports Admissions information Undergraduate admissions overview Open days and events Undergraduate course overview overview Making your application Admissions FAQs Super curricular activities MPhil in Advanced Computer Science overview Applications Course structure Funding competitions Prerequisites PhD in Computer Science overview Application forms Research Proposal Funding competitions and grants Part-time PhD Degree Premium Research Studentship Current students overview Part IB overview Part IB group projects overview Important dates Design briefs Moodle course ➥ Learning objectives and assessment Technical considerations After the project Part II overview Part II projects overview Project suggestions Project Checker groups Project proposal Advice on running the project Progress report and presentation The dissertation Supervisor briefing notes Project Checker briefing notes Past overseer groups ➥ Part II Supervision sign-up Part II Modules Part II Supervisions overview Continuing to Part III overview Part III of the Computer Science Tripos Overview overview Information for current Masters students overview Special topics Part III and ACS projects overview Submission of project reports ACS projects overview Guidance for ACS projects Part III projects overview Guidance for Part III projects Preparation Registration Induction - Masters students PhD resources overview Deadlines for PhD applications Protocol for Graduate Advisers for PhD students Guidelines for PhD supervisors Induction information overview Important Dates Who is here to help Exemption from University Composition Fees Being a research student Researcher Development Research skills programme First Year Report: the PhD Proposal Second Year Report: Dissertation Schedule Third Year Report: Progress Statement Fourth Year: writing up and completion overview PhD thesis formatting Writing up and word count Submitting your dissertation Papers and conferences Leave to work away, holidays, and intermission List of PhD students ➥ PAT, recycling, and Building Services Freshers overview Cambridge University Freshers' Events Undergraduate teaching information and important dates Course material 2023/24 ➥ Course material 2024/25 ➥ Exams overview Examination dates Examination results ➥ Examiners' reports ➥ Part III Assessment MPhil Assessment Past exam papers ➥ Examinations Guidance 2023-24 Marking Scheme and Classing Convention Guidance on Plagiarism and Academic Misconduct Purchase of calculators Examinations Data Retention Policy Guidance on deadlines and extensions Mark Check procedure and Examination Review Lecture timetables overview Understanding the concise timetable Supervisions overview Part II supervisions overview ➥ Part II supervision sign-up ➥ Supervising in Computer Science Supervisor support Directors of Studies list Academic exchanges Advice for visiting students taking Part IB CST Summer internship: Optimisation of DNN Accelerators using Bayesian Optimisation UROP internships Resources for students overview Student SSH server Online services Managed Cluster Service (MCS) Microsoft Software for personal use Installing Linux Part III and MPhil Machines Transferable skills Course feedback and where to find help overview Providing lecture feedback Fast feedback hotline Staff-Student Consultative Forum Breaking the silence ➥ Student Administration Offices Intranet overview New starters and visitors Forms and templates Building management Health and safety Teaching information Research admin Miscellaneous Undergraduate admissions MPhil in Advanced Computer Science The Department of Computer Science and Technology will offer a part-time route to the PhD Degree with effect from October 2022.  Part-time structure The Department of Computer Science and Technology could offer a part-time route to the PhD. At present, the University allows a part-time route which is 60% or 75% of a fulltime PhD route for which the minimum number of terms:  60% route -15 terms minimum; maximum number of terms for a part-time student is 21 terms.  75% route - 12 terms minimum; maximum number of terms for a part-time student is 16 terms. The requirements for the probationary CPGS in Computer Science will be spread across two years with the first-year report due near the end of the fifth term (i.e. end of March for a Michaelmas admittee), and the registration viva occurring in the sixth term (Easter term). The Department expects the completion of the required 12 units from the Researcher Skills Programme across two years. Part-time students are also encouraged to spend one term full-time in the first year of the programme and that students will be in residence in Cambridge during that time. After successful registration for the PhD Degree, part-time Ph.D. students are expected to have between 2 and 4 meetings with their supervisor per term for at least a further ten terms. They are expected to spend an average of three weeks each term in the Department with a minimum of 45 nights p.a. in residence. Requirements for a part-time PhD applicants in Computer Science and Technology The proposed topic needs to be suitable for study over a minimum of 12 or 15 terms (75% or 60% route respectively) and a maximum of 16 or 21 terms (75% or 60% route respectively) . Applicants will need to provide a schedule of the research over the first few years.  If a supervisor identifies a potential student and a topic as being possibly suitable for part-time study, an initial interview report form must be sent to the PhD Applications Panel for consideration. Potential supervisors should invite the Chair of the PhD Applications Panel or a deputy to attend the formal interview. As well as consideration by the PhD Applications Panel, the interview report will be considered by, and a decision approved by, the Degree Committee. The approved form will also be loaded to the applicant portal for consideration by the Postgraduate Admissions Office. The proposed supervisor must be able to supervise a part-time Ph.D. for at least the minimum 15 terms. This means that supervisors on short-term contracts, or those due to retire within seven years of a part-time student being admitted, will not be eligible to supervise. Those who are due to take sabbatical leave should consider alternative supervision arrangements. Applicants should be aware that there is no obligation on supervisors to accept applicants who wish to be admitted as part-time students. The student must live close enough to Cambridge, or be able to spend enough time in Cambridge during the first two years, to be able to participate, as much as possible, in research group seminars, reading groups and other activities. The student and supervisor will sign an agreement about how often the student will be in the department. This might be, for example : 2 x 8-hour days per working week per term, or 3 x 1-week per term, plus 40% of time in the research term (1 July to 30 September). Most CST Research Skills courses are available remotely. For research themes’ group meetings and seminars, physical presence in the department is preferred. The student will be required to provide a letter from the employer (if the student is employed) confirming that they may have time off to attend the University as required for the duration of the course. Applicants are required to upload a part-time attendance Declaration to their application once approved for admission. Updated May 2024 Department of Computer Science and Technology University of Cambridge William Gates Building 15 JJ Thomson Avenue Cambridge CB3 0FD Information provided by [email protected] Privacy policy Social media © 2024 University of Cambridge Contact the University Accessibility Freedom of information Privacy policy and cookies Statement on Modern Slavery Terms and conditions University A-Z Undergraduate Postgraduate Research news About research at Cambridge Spotlight on... CRA-I Welcomes New Leadership! It is July 1st, which means it is CRA-Industry (CRA-I)’s first official change in leadership! We are delighted to welcome Divesh Srivastava and Fatma Özcan as our new Co-chairs!  Fatma and Divesh will take over for Vivek Sarkar (Georgia Tech) and Ben Zorn (Microsoft) who did a tremendous job serving as CRA-I’s initial Co-chairs starting in 2021. They were chartered by the CRA Board to stand up the new Industry-focused committee and have grown it from just an idea to its current state – a full Steering Committee and (almost full) Council made up of 17 different companies and institutions of different sizes. We thank them for their service, and for turning CRA-I into an asset for the entire computing research community. Privacy Overview This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful. You can adjust all of your cookie settings. Information for Prospective M.S. Students Ms in computer science. Our Master of Science program is designed for individuals considering a career in computer science that requires research skills and rigorous training, but who are unsure if they are ready to commit to a Ph.D. program. The coursework is identical to that offered to our Ph.D. students.  MS Degree Requirements The Graduate Policy Manual details all of the information on degree requirements, but in summary,our graduate students receive the training and are expected to develop a mastery of their field and gain a broad familiarity with their discipline by the time they graduate. Admission criteria are similar to those of the Ph.D. program.  Coursework: 30 credit hours of qualifying courses covering four out of the eight areas. Research: Research is expected, but students can choose between two options: Non-thesis: Requires a scholarly paper of journal or conference quality, under computer science faculty supervision. Students may optionally replace up to six credits with CMSC 798 (Master’s Non-thesis Research). Thesis: Requires six hours of CMSC 799 (Master's Thesis Research) and write a thesis advised by a computer science faculty member. The thesis must demonstrate an independent accomplishment in a research, development, or application area of computer science. An oral examination (Thesis Defense) is required to graduate.  The thesis option requires finding an advisor and a research topic within the specified time frame. The non-thesis option is the default option due to its more flexible requirements.  Program Duration The MS program typically takes two years. However, UMD Computer Science undergraduates eligible for our Combined BS/MS program may finish the program in one year.  Note: Students eligible for the Combined BS/MS program should list their degree intent as the Combined BS/MS program when applying. Financial Information While the MS program does not guarantee funding as part of the admission offer. MS students may apply for hourly CMSC TA opportunities, RA opportunities with faculty members, or other jobs on campus. Hourly TA Positions: MS students can apply for hourly CMSC TA opportunities with no graduate assistantship benefits, tuition remission or health insurance. Campus Employment Opportunities: Beyond Computer Science (CMSC) RA roles, MS students can pursue RA, TA, or Administrative Assistant (AA) opportunities across different programs. These opportunities are listed on ejobs.umd or Handshake . Research Assistants (RA): All M.S. students, including first-year students, are eligible for graduate assistantship appointments. Faculty members may appoint them as Research Assistants (RAs) depending on their research needs and available funding.  Tuition and Fees For detailed information about tuition rates and related expenses, please visit the Office of Extended Studies website . Fellowships Fellowships can be sourced both from within the University of Maryland and through external organizations: Internal Fellowships: Offered directly by UMD or specific departments within the university. For details on these opportunities, you can check out UMD's Fellowship & Awards website . External Fellowships: Examples include prestigious awards like the National Science Foundation Graduate Fellowships and Fulbright Fellowships . To apply for these, students should directly contact the administering agencies or seek assistance from the financial aid office at their current or UMD’s Fellowship Office . To apply for these fellowships, you should contact the agency which administers them, check with the financial aid office in your current university, or contact UMD's Fellowship Office . Comment Comments Save Article Read Later Read Later The Year in Computer Science December 20, 2023 Video : In 2023, computer scientists made progress on a new vector-driven approach to AI, fundamentally improved Shor’s algorithm for factoring large numbers, and examined the surprising and powerful behaviors that can emerge from large language models. Myriam Wares for Quanta Magazine (cover); Emily Buder/ Quanta Magazine and Taylor Hess and Noah Hutton for Quanta Magazine (video) Introduction In 2023, artificial intelligence dominated popular culture — showing up in everything from internet memes to Senate hearings. Large language models such as those behind ChatGPT fueled a lot of this excitement, even as researchers still struggled to pry open the “black box” that describes their inner workings. Image generation systems also routinely impressed and unsettled us with their artistic abilities, yet these were explicitly founded on concepts borrowed from physics . The year brought many other advances in computer science. Researchers made subtle but important progress on one of the oldest problems in the field, a question about the nature of hard problems referred to as “P versus NP.” In August, my colleague Ben Brubaker explored this seminal problem and the attempts of computational complexity theorists to answer the question: Why is it hard (in a precise, quantitative sense) to understand what makes hard problems hard? “It hasn’t been an easy journey — the path is littered with false turns and roadblocks, and it loops back on itself again and again,” Brubaker wrote. “Yet for meta-complexity researchers, that journey into an uncharted landscape is its own reward.” The year was also full of more discrete but still important pieces of individual progress. Shor’s algorithm, the long-promised killer app of quantum computing, got its first significant upgrade after nearly 30 years. Researchers finally learned how to find the shortest route through a general type of network nearly as fast as theoretically possible . And cryptographers, forging an unexpected connection to AI, showed how machine learning models and machine-generated content must also contend with hidden vulnerabilities and messages . Some problems, it seems, are still beyond our ability to solve — for now. Tommy Parker for Quanta Magazine Hard Questions, Hard Answers For 50 years, computer scientists have tried to solve the biggest open question in their field, known as “P versus NP.” It asks, roughly, how hard certain hard problems are. And for 50 years, their attempts have ended in failure. Many times, just as they began to make progress with a new approach, they hit a barrier proving that the tactic would never work. Eventually, they began to wonder why it’s so hard to prove that some problems are hard. Their efforts to answer such inward-looking questions have blossomed into a subfield, called meta-complexity, which has provided the greatest insights into the question yet. In an August article and a short documentary video , Quanta explained exactly what we know, how we know it and what we’re just starting to figure out when it comes to meta-complexity. At stake is not just the curiosity of the researchers involved: Resolving P versus NP could solve countless logistical problems, render all cryptography moot, and even speak to the ultimate nature of what’s knowable and what’s forever beyond our grasp. Paul Chaikin/Quanta Magazine The Powers of Large Language Models Get enough stuff together, and you might be surprised by what can happen. Water molecules create waves, flocks of birds swoop and soar as one, and unconscious atoms combine into life. Scientists call these “emergent behaviors,” and they’ve recently seen the same thing happen with large language models — AI programs trained on enormous collections of text to produce humanlike writing. After they reach a certain size, these models can suddenly do unexpected things that smaller models can’t, such as solving certain math problems . Yet the surge of interest in large language models has raised new concerns. These programs invent falsehoods, perpetrate social biases , and fail to handle even some of the most elementary elements of human language. Moreover, these programs remain a black box, their internal logic unknowable, though some researchers have ideas about how to change that . Samuel Velasco/ Quanta Magazine Solving Negativity Computer scientists have long known of algorithms that can whiz through graphs — networks of nodes connected by edges — where the connections have some cost, like a toll road connecting two cities. But for decades, they couldn’t find any fast algorithm for determining the shortest path when a road could have either a cost or a reward. Late last year, a trio of researchers delivered a workable algorithm that’s nearly as fast as theoretically possible. Then in March, researchers posted a new algorithm that can determine when two types of mathematical objects known as groups are the same in a precise way; the work may lead to algorithms that can quickly compare groups (and perhaps other objects) more generally, a surprisingly difficult task. Other big algorithm news this year included a new way of computing prime numbers by incorporating random and deterministic approaches, the refutation of a long-standing conjecture about the performance of information-limited algorithms, and an analysis that shows how an unintuitive idea can improve the performance of gradient descent algorithms, which are ubiquitous in machine learning programs and other areas. Samuel Velasco/ Quanta Magazine ; source: Shutterstock Appreciating AI Art Image-generating tools like DALL·E 2 exploded in popularity this year. Simply feed them a written prompt, and they’ll spit back a tableau of art depicting whatever you requested. But the work that made most of these artificial artists possible had been brewing for many years . Based on concepts from physics that describe spreading fluids, these so-called diffusion models effectively learn how to unscramble formless noise into a sharp image — as if turning back the clock on a cup of coffee to see the evenly distributed cream reconstitute into a well-defined dollop. AI tools have also been successful in improving the fidelity of existing images , though we’re still far from the TV trope of a cop repeatedly shouting “Enhance!” More recently, researchers have turned to physical processes besides diffusion to explore new ways for machines to generate images. A newer approach governed by the Poisson equation, which describes how electric forces vary over distance, has already proved more capable of handling errors and is easier to train than diffusion models, in some cases. DVDP for  Quanta Magazine Improving the Quantum Standard For decades, Shor’s algorithm has been the paragon of the power of quantum computers. Developed by Peter Shor in 1994, this set of instructions allows a machine that can exploit the quirks of quantum physics to break large numbers into their prime factors much faster than a regular, classical computer — potentially laying waste to much of the internet’s security systems. In August, a computer scientist developed an even faster variation of Shor’s algorithm, the first significant improvement since its invention. “I would have thought that any algorithm that worked with this basic outline would be doomed,” Shor said. “But I was wrong.” Yet practical quantum computers are still beyond reach. In real life, tiny errors can quickly add up, ruining calculations and taking away any quantum benefits. In fact, late last year, a team of computer scientists showed that for a specific problem, a classical algorithm does roughly as well as a quantum one that includes errors. But there is hope: Work in August showed that certain error-correcting codes, known as low-density parity check codes, are at least 10 times more efficient than the current standard. Harol Bustos for Quanta Magazine Hiding Secrets in AI In an unusual finding at the intersection of cryptography and artificial intelligence, a team of computer scientists showed it was possible to insert into machine learning models certain backdoors that were practically invisible, their undetectability backed up by the same logic as the best modern encryption methods. The researchers focused on relatively simple models, so it’s unclear whether the same holds true for the more complicated models behind much of today’s AI tech. But the findings do suggest ways for future systems to guard against such security vulnerabilities, while also signaling a renewed interest in how the two fields can help each other grow. These kinds of security issues are part of the reason Cynthia Rudin has championed using interpretable models to better understand what’s happening inside machine learning algorithms; researchers like Yael Tauman Kalai , meanwhile, have advanced our notions of security and privacy, even in the face of looming quantum technology. And a result in the related field of steganography showed how to hide a message with perfect security within machine-generated media. Myriam Wares for Quanta Magazine Vector-Driven AI As powerful as AI has become, the artificial neural networks that underpin most modern systems share two flaws: They require tremendous resources to train and operate, and it’s too easy for them to become inscrutable black boxes. Many researchers argue that perhaps it’s time for another approach . Instead of using artificial neurons that detect individual traits or characteristics, AI systems could represent concepts with endless variations of hyperdimensional vectors — arrays of thousands of numbers. This system is more versatile and better equipped to handle errors, making its computations far more efficient, and it allows researchers to work directly with the ideas and relationships these models consider, giving them greater insight into the model’s reasoning. Hyperdimensional computing is still in its infancy, but as it gets put to bigger tests, we may see the new approach start to take hold. Get highlights of the most important news delivered to your email inbox Comment on this article Quanta Magazine moderates comments to facilitate an informed, substantive, civil conversation. Abusive, profane, self-promotional, misleading, incoherent or off-topic comments will be rejected. Moderators are staffed during regular business hours (New York time) and can only accept comments written in English.  Next article Machine Learning & Data Science Foundations Online Graduate Certificate Apply to Expand Your Future As the value of data continues to skyrocket, companies are in need of people who can transform large data sets into rich analytical insights. Now, you can learn these techniques in Carnegie Mellon’s cutting-edge online program. Apply today to expand your future in machine learning and data science.   Are we the right fit?   Let’s face it, pursuing any kind of advanced training is an investment of your time, energy and resources. Before you consider our program, make sure your background aligns with our program expectations.   Successful applicants will have: A bachelor’s degree in STEM or related field  Successful applicants will hold a degree in a science, technology, engineering or math-related field. Other degrees will be considered if the applicant can show the necessary proficiency in math and programming.   Proficiency in advanced math  Students should provide evidence of successful completion of advanced math coursework such as calculus, linear algebra and statistics.   Proficiency in programming  Students should be proficient in Python, R, or an analogous programming language, with experience writing at least 1000 lines of code.   Relevant work experience   Ideally, applicants will have some relevant work experience in either computer programming or a related field. Internships or other related work are acceptable.   A disciplined and motivated mindset  Harder to measure, but equally important, successful applicants will have a resilient spirit, a hunger to learn, and a knack for solving problems through technical innovation. With courses taught by CMU faculty from the #4 computer science school in the country, a consistent and conscious effort will be required to master each topic. If you have questions about the program or how it aligns with your background, please call 412-501-2686 or send an email to  [email protected]  with your inquiries . Application Requirements Ready to apply? Here’s what you’ll need to complete the admissions process:  ✔ Complete the online application Submit your application in the application portal. ✔ Submit your resume/CV We’d like to learn more about your employment history, academic background, technical skills, and professional achievements. Submit a 1 to 2 page resume or CV showcasing your experience.  ✔ Submit your transcripts Submit an unofficial copy of your transcript for each school you attended. Transcripts must include your name, the name of the college or university, the degree awarded (along with the conferral date), as well as the grade earned for each course. Email your transcripts directly to [email protected] .   ✔  Upload a statement of purpose Tell us your professional story. Where have you been, and where do you hope to go? In 500 words or less, please share how our program would advance your capabilities in your current role or prepare you for a new role in the industry.  ✔ Submit your TOEFL, IELTS, or DuoLingo test scores An official TOEFL, IELTS, or DuoLingo test is required for non-native English speakers. This requirement will be waived, however, for applicants who either completed an in-residence bachelor’s, master’s, or doctoral degree program in the United Kingdom, United States, or Canada (excluding Quebec) or have at least three years of professional work experience using English as their primary language. If you fall into one of these categories, please include this information on your resume.   Tuition: Invest in Your Future By enrolling in our graduate-level program, you'll be investing in your professional growth to expand your skillset or advance your career. We know this is a significant investment. Not just for you, but for your family as well. Scholarships To help offset the cost of tuition, and to make our program as accessible as possible, we offer a limited number of partial, merit-based scholarships. All applications will be evaluated for these awards automatically; there is no need to submit additional materials. If you are awarded a scholarship, you will be notified in your decision letter.  All applicants who submit by the priority deadline will receive a partial scholarship award. In addition, Carnegie Mellon alumni are eligible for a scholarship to the Graduate Certificate in Machine Learning & Data Science Foundations worth up to 20% of tuition. Indicate your alumni status within the application to be eligible. So, what is the investment per course? Below is a breakdown of our tuition for the 2024/2025 academic year: Course Units Investment Mathematical Foundations of Machine Learning 6 units $4,242 Computational Foundations for Machine Learning 6 units $4,242 Python for Data Science (Part 1) 6 units $4,242 Python for Data Science (Part 2) 6 units $4,242 Foundations of Computational Data Science (Part 1) 6 units $4,242 Foundations of Computational Data Science (Part 2) 6 units $4,242 Total Investment An additional technology fee of approximately $230 will be assessed each semester. The rates above are for the 2024/2025 academic year only. If the program is not completed within that time frame, tuition may increase slightly for the following academic year. Financing Your CMU Graduate Certificate Monthly payment plan. CMU provides a monthly payment option , managed by Nelnet Campus Commerce, designed to help students spread out tuition payments into manageable monthly installments. This plan also offers the ease of online enrollment. Should you be admitted and choose to join us, we recommend registering for this plan early to fully benefit from the range of payment options available. Financial Aid & Private Loans Students pursuing a graduate certificate are not eligible to receive federal financial aid. However, private loans are a viable alternative to consider with competitive interest rates and borrower benefits. See FastChoice , a free loan comparison service to easily research options. Employer Tuition Reimbursement Many companies offer tuition reimbursement programs to foster professional development among their employees. We encourage you to contact your HR department to find out if similar opportunities exist at your workplace.  When you speak to your employer, you can share that our program:  Consists of transcripted, credit-bearing courses (not just continuing education units). You will earn 36 Carnegie Mellon graduate-level credits when you complete the full program.   Equips you with foundational skills in AI, machine learning, and computational data science, which means you’ll be ready to extract meaningful insights from large, complex data sets right from the get-go. With the #1 program in Artificial Intelligence and the #1 Programming Languages school in the country, CMU is the ideal place to learn these skills and techniques. Features coursework taught by CMU faculty experts who are spearheading research in language technologies, computer science, machine learning, and human-computer interaction.  Is delivered completely online , which means you can take classes on your own time while maintaining your normal work schedule. Not sure how to approach your employer? Need specific documents to proceed with enrollment?  Call 412-501-2686 or send an email to  [email protected]  with your inquiries .  We’re here to help you take the next step in your professional  journey.  CMU EMPLOYEE TUITION REIMBURSEMENT The Graduate Certificate in Machine Learning & Data Science Foundations is eligible for CMU tuition remission. Review the   CMU tuition remission policy   to check your eligibility. A Note for International Applicants As part of a global university with locations and students from around the world, the School of Computer Science welcomes the diverse perspectives that international students bring to our programs. The Graduate Certificate in Machine Learning & Data Science Foundations provides a unique opportunity for individuals nearly everywhere to earn a certificate at the intersection of AI, machine learning, and computational data science from one of the top ranked computer science schools in the country.  To help ensure you are fully prepared for the admissions process and, if admitted, for success as a student, this section provides detailed information about requirements for international applicants. We look forward to reviewing your application. The Graduate Certificate in Machine Learning & Data Science Foundations considers for admission international applicants who reside within, or outside of, the domestic United States. International applicants who reside within or outside of the domestic United States are advised of the following information and additional requirements for international applicants to the program. Student Visas Since this program is fully online, enrollment in this program will not qualify students for any type of visa to enter or remain in the United States for any purpose.  Time and Attendance Requirement   Classes for the program will be taught on the U.S. Eastern Time zone schedule, and students must be available to attend all live classes, regardless of location. U.S. Sanctions; U.S. Sanctioned Countries Individuals who are the target of U.S. sanctions or who are ordinarily resident in a U.S. sanctioned country or who live or expect to live in a U.S. sanctioned country while participating in the program are not eligible for admission to this program due to legal restrictions/prohibitions and should not apply. U.S sanctioned countries are currently Belarus, Cuba, Iran, North Korea, Russia, Syria and the following regions of Ukraine: Crimea, Donetsk and Luhansk. In addition, all or a portion of this program may not be available to individuals who are ordinarily resident of certain countries due to legal restrictions.   Applications received from these individuals will not be accepted. As well, if an individual is admitted to the program and subsequently the individual becomes the target of U.S. sanctions, ordinarily resident of a U.S. sanctioned country or lives in a U.S. sanctioned country while participating in the program (or otherwise becomes ordinarily resident of country in which the program is not available due to legal restrictions), the individual’s continued enrollment in the program may be terminated and/or restricted (due to U.S. legal restrictions/prohibitions) and the individual may not be able to complete the program.   Licensure in Various Jurisdictions From time to time Carnegie Mellon reviews the licensing requirements of various jurisdictions in order to assess whether Carnegie Mellon may be precluded from making the program available to applicants that are residents of one or more of these jurisdictions prior to Carnegie Mellon obtaining the relevant license(s). Affected applicants from these jurisdictions, if any, will be notified prior to enrollment if Carnegie Mellon determines that it is unable to make the program available to them for this reason. Value Added Tax (VAT) and Other Taxes The tuition, required fees and other amounts quoted for this program do not include charges for applicable Taxes (hereinafter defined). The student is responsible for payment of all applicable Taxes (if any) relating to the tuition, required fees and other amounts required to be paid to Carnegie Mellon for the program, including any Taxes payable as a result of the student’s payment of such Taxes.  Further, the student must timely make all payments due to Carnegie Mellon without deduction for Taxes, unless the deduction is required by law. If the student is required under applicable law to withhold Taxes from any payment due to Carnegie Mellon, the student is responsible for timely (i) paying to Carnegie Mellon such additional amounts as are necessary so that Carnegie Mellon receives the full amount that it would have received absent such withholding, and (ii) providing to Carnegie Mellon all documentation, if any, necessary to permit the student and/or Carnegie Mellon to claim the application of available tax treaty benefits (for Carnegie Mellon review and completion, if warranted and acceptable).  Taxes mean any taxes, governmental charges, duties, or similar additions or deductions of any kind, including all use, income, goods and services, value added, excise and withholding taxes assessed by or payable in the student’s country of residence and/or country of payment (but does not include any U.S. federal, state or local taxes). What kind of academic background do I need? Successful applicants will have a bachelor’s degree in a STEM-related field. Other degrees will be considered if the applicant can show the necessary proficiency in math and programming. Applicants should also have proficiency in programming languages like Python or R, with experience writing up to 1000 lines of code.  Do I need work experience? Applicants will ideally have some relevant work experience in either computer programming or a related field. Internships or other related work are also acceptable. What materials do I need to submit when I apply to this program? Besides the online application, applicants must submit a current resume, transcripts, and a personal statement to be considered for enrollment. Is there an application fee? No, this program does not require an application fee. When is the application deadline?  All applicants who submit by the priority deadline of July 9, 2024 will receive a partial scholarship award. The final deadline to apply is July 30, 2024. How do I check the status of my application? You can view the status of your application at any time in the application portal. A decision letter from Carnegie Mellon will be sent through the application portal within a few weeks of submitting your online application. After I submit my application, when will I hear back? You’ll receive a decision letter within a few weeks of submitting your application. Is a deposit required to secure my spot? No, a deposit is not required to secure your spot in the program. If I choose to complete the entire certificate, what is my total investment? The total investment for the Machine Learning & Data Science Foundations certificate during the 2024/2025 academic year is $25,452. A breakdown of the tuition and fees can be found above. Partial scholarships are available. All applicants who submit by the priority deadline of July 9, 2024 will receive a partial scholarship award. Carnegie Mellon alumni are eligible for a scholarship to the Graduate Certificate in Machine Learning & Data Science Foundations worth up to 20% of tuition. Is this program eligible for CMU tuition remision? Yes, the Graduate Certificate in Machine Learning & Data Science Foundations is eligible for CMU tuition remission. Review the   CMU tuition remission policy   to check your eligibility. Application Deadlines Priority*: July 9, 2024 Final: July 30, 2024 *All applicants who submit by the priority deadline will receive a partial scholarship award. Request Info Questions? There are two ways to contact us. Call 412-501-2686 or send an email to  [email protected] with your inquiries. Fast Admission Decisions Applications are evaluated on a bi-weekly basis, which means you’ll receive a decision letter fast,  within a few weeks  of submitting your application .   At CMU, we recognize the value of time well spent. Quick decisions mean less time wasted and more time preparing for your future. Due to the individual nature of the coursework, space is limited for our program - applications will be accepted until the class is full. 255 IMAGES 2024 Best Part Time PhD in Computer Science Programs How To Phd In Computer Science 2024 Part Time PhD in Computer Science Programs PhD in Computer Science: Specializations & Best Degrees All you need to know about PhD in Computer Sciences 2024 Part Time PhD in Computer Science Programs VIDEO HPU PHD Computer Science Entrance Question Paper Only Get your PhD while doing a Job! BPSC Computer Science Teacher AMU PHD ENTRANCE PAPERS l PHD computer Science B paper l amu phd papers Computer Fundamental Concept BPSC Computer Science Teacher COMMENTS PhD Admissions The Computer Science Department PhD program is a top-ranked research-oriented program, typically completed in 5-6 years. 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SCS faculty are esteemed in their field, and many of them have collaborated on ... The Year in Computer Science The year brought many other advances in computer science. Researchers made subtle but important progress on one of the oldest problems in the field, a question about the nature of hard problems referred to as "P versus NP." ... Many researchers argue that perhaps it's time for another approach. Instead of using artificial neurons that ... Apply to CMU's Online Graduate Certificate in Machine Learning and Data The Graduate Certificate in Machine Learning & Data Science Foundations provides a unique opportunity for individuals nearly everywhere to earn a certificate at the intersection of AI, machine learning, and computational data science from one of the top ranked computer science schools in the country. essay homework paper phd project resume review speech study thesis