phd position in information science

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information science PhD Projects, Programmes & Scholarships

A taste of home: exploring migrating food heritage and food information practices, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Self-Funded PhD Students Only

This project does not have funding attached. You will need to have your own means of paying fees and living costs and / or seek separate funding from student finance, charities or trusts.

The use digital tools and online information for the self-management of health

A new model for information literacies of community representatives, trust, risk and digital identity for digitally-unsure citizens, deep-learning for semantic-based information extraction from natural language, ai to the rescue of climate change, modelling air quality for cleaner urban planning, using ontologies to explain ai based risk assessment, fully funded phd positions in astronomy, biology, computer science, chemistry & materials, data science & scientific computing, earth science, mathematics, neuroscience, and physics, funded phd programme (students worldwide).

Some or all of the PhD opportunities in this programme have funding attached. Applications for this programme are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full programme details for further information.

International PhD Programme

International PhD programs are often designed for international students. Your PhD will usually be delivered in English, though some opportunities to gain and use additional language skills might also be available. Students may propose their own PhD topics or apply for advertised projects.

School of Computing Science

Computing phd programme.

PhD Research Programmes describe the opportunities for postgraduate research within a University department. You may often be asked to submit your own research project proposal as part of your application, although predefined research projects may also be available.

Smart sensors and spectral techniques in human movement science

Privacy violation and cyber security issues in digital media misinformation during environmental and health crises, an experimental cybersecurity study of human factors in phishing attack susceptibility, a decentralized, data driven health monitoring and diagnostics platform based on artificial intelligence (ai) and wearable/portable internet of medical things (iomt) sensors, ontological modelling for data analysis, detection and prevention of ransomware attacks targeting iiot (industrial internet of things) devices and networks.

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Ph.D. in Information and Library Science

This doctoral program provides an environment that enables creative and energetic students to become innovative thinkers and leaders. Through coordination of student and faculty interests and activities, the program offers opportunities for research, teaching, and leadership in a variety of settings.

Information and library science research leaders must be able to identify problems that are significant for our future as an information society, carry out rigorous studies and draw valid conclusions from them, and communicate those findings to stakeholders who can act on them. The SILS doctoral program provides intensive, but highly flexible and customizable, preparation for careers in academia and research.

The Ph.D. in Information and Library Science is designated as a STEM program, which allows eligible international graduates to apply for a 24-month OPT extension.

After successfully defending their dissertations, SILS’ graduates have accepted positions as tenure-track faculty in information schools, research scientists in corporate and government labs, and chief information officers in a myriad of organizations and businesses. With a degree from our doctoral program, our graduates are making a difference.

• Kimberly Hirsh, 2021, Consulting Scholar-Librarian
• Sandeep Avula, 2020, Research Scientist, Amazon
• Eliot Hauser, 2020, Assistant Professor, University of Texas at Austin
• Colin Post, 2020, Assistant Professor, University of North Carolina at Greensboro
• Jonathan Crabtree, 2020, Assistant Director of Research Data Information Systems, Odum Institute, UNC-CH
• Emily Roscoe, 2020, Adjunct Instructor, School of Government, UNC-CH
• Megan Threats, 2020, Assistant Professor, Rutgers University
• Heather Barnes, 2020, Digital Curation Librarian, Wake Forest University
• Yinglong Zhang, 2020, Research Scientist, Google
• Shenmeng Xu, 2020, Scholarly Communications Librarian, Vanderbilt University
• Sarah Beth Nelson, 2019, Assistant Professor, University of Wisconsin, Whitewater
• Anita Crescenzi, 2019, Assistant Professor, School of Pharmacy, UNC-CH
• Kathleen Brennan, 2018, Senior Researcher, Google
• Samantha Kaplan, 2018, Research and Education Librarian, Duke University
• Ericka Patillo, 2018, Clinical Assistant Professor, School of Information Studies, University of Tennessee, Knoxville
• Grace Shin, 2018, Sookmyung Women’s University, Korea, Adjunct Professor at SILS.
• Leslie Thomson, 2018, Postdoctoral Fellow, UNC-CH

Other notable graduates in recent years:

• Jay Dominick, 2005 , Vice President and CIO at Princeton University
• Meredith Evans, Ph.D.  2006 , Director, Jimmy Carter Presidential Library and Museum & 74th President of the Society of American Archivists
• Meredith Weiss, 2010 , Vice President for Administration at Virginia Commonwealth University
• Fred Stutzman, 2011 , CEO, Freedom

Financial Support

SILS typically provides support for full-time doctoral students during their first five years of study. Prospective doctoral students must apply by December 10 to receive full consideration for financial aid.

Learn more from our Financial Information page.

SILS seeks PhD students who:

• Aim to be information leaders in the 21 st century.
• Are attracted to information and library science as a field that incorporates diverse theoretical perspectives and a wide range of research methods.
• Possess the discipline and will to be independent investigators, and the vision and communication skills to be influential leaders in the field.
• Are committed to a life of research and scholarly inquiry addressing critical questions.
• Enjoy intellectual challenges and demonstrate analytical and critical thinking.

Admission to the doctoral program is competitive and based upon the strength of the applicant’s educational background and standardized test scores, work experience, statement of research, and personal interview. In reviewing applicants for admission, the school will consider past academic record and scholarly potential of an applicant, as well as the match of the candidate’s research interests with those of the school’s faculty. One or more faculty must be willing to assume the advisory role for the student.

Doctoral and Special Programs Coordinator

[email protected] or 919-962-0182

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The School of Information is UC Berkeley’s newest professional school. Located in the center of campus, the I School is a graduate research and education community committed to expanding access to information and to improving its usability, reliability, and credibility while preserving security and privacy.

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The School of Information offers four degrees:

The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.

The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS degree for Cal undergraduates.

The Master of Information and Cybersecurity (MICS) is an online degree preparing cybersecurity leaders for complex cybersecurity challenges.

Our Ph.D. in Information Science is a research program for next-generation scholars of the information age.

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The School of Information's courses bridge the disciplines of information and computer science, design, social sciences, management, law, and policy. We welcome interest in our graduate-level Information classes from current UC Berkeley graduate and undergraduate students and community members.  More information about signing up for classes.

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• User Experience Research

Research by faculty members and doctoral students keeps the I School on the vanguard of contemporary information needs and solutions.

The I School is also home to several active centers and labs, including the Center for Long-Term Cybersecurity (CLTC) , the Center for Technology, Society & Policy , and the BioSENSE Lab .

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Ph.D. in Information Science

Ph.d. community.

Ph.D. students are knowledge architects and respected contributors to our information society, with a vision of expanding access to quality information, an appreciation for diverse perspectives, and the spirit of collaboration.

You Belong at Berkeley

The I School is a welcoming community of students, faculty, and staff from a wide variety of backgrounds, nations, cultures, and experiences.

The doctoral program is a research-oriented program in which the student chooses specific fields of specialization, prepares sufficiently in the literature and the research of those fields to pass a qualifying examination, and completes original research culminating in the written dissertation. The degree of Doctor of Philosophy is conferred in recognition of a candidate's grasp of a broad field of learning and distinguished accomplishment in that field through contribution of an original piece of research revealing high critical ability and powers of imagination and synthesis.

The Ideal Place for Breakthrough Thinking

School of Information offers an ideal environment for information scholars , on the campus of a preeminent, forward-thinking research institution .

Dedicated to cross-disciplinary research, breakthrough thinking, and creative collaboration, the I School actively shapes the information frontier and has a track record of scholarly ideas, solutions, and policy counsel that make information more accessible, manageable, and useful.

Rigorous academics instill the theoretical and research capabilities required to advance diverse interests — from information design, architecture, and assurance, to human-computer interaction and the social, economic, and public policy implications of information. Ph.D. students work closely with faculty recognized as information pioneers.

Interdisciplinary thinking and partnership are central to the I School approach, so doctoral research often engages exceptional UC Berkeley schools and departments beyond the I School, from journalism, business, and law to computing, engineering, humanities, and social sciences.

On average, I School students complete the Ph.D. degree in 6 years.

• Semester 1–4 : Breadth, major, & minor coursework
• Semester 4–5 : Prelim research paper & exam
• Semester 6–8 : Qualifying exam
• Semester 10–12 : Complete & present dissertation

Detailed degree requirements & timeline

Areas of Study

Major and minor areas include:

• Human-Computer Interaction
• Information Economics and Policy
• Information Law and Policy
• Information Organization and Retrieval
• Information Systems Design
• Social Aspects of Information
• Information and Communication Technologies and Development

Your Career

I School Ph.D. graduates go on to careers in academia, industry, or the public sector.

Recent Ph.D. graduates hold tenure-track faculty positions at the world’s leading universities, as well as leading research positions in industry, academia, and public-interest organizations.

More about Ph.D. career outcomes

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“I think we can do a better job of using the Internet to tap into how people are doing, how they’re feeling, and what matters to them — online democracy, in a way, but minus the hype.”

—Galen Panger Ph.D. 2017

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Information Science: PhD

About the Program

The doctoral program.

The doctoral program in Information Science is a research-oriented program in which the student chooses specific fields of specialization, prepares sufficiently in the literature and the research of those fields to pass a qualifying examination, and completes original research culminating in the written dissertation. The degree of Doctor of Philosophy is conferred in recognition of a candidate's grasp of a broad field of learning and distinguished accomplishment in that field through the contribution of an original piece of research revealing high critical ability and powers of imagination and synthesis.

The I School also offers a master's in Information Management and Systems (MIMS), a master's in  Information and Data Science  (MIDS), and a master's in  Information and Cybersecurity (MICS).

Visit School Website

Admission to the PhD Program

We welcome students from a diverse set of backgrounds; some will be technically educated, some educated in the humanities and social sciences.

The I School typically accepts 3-7 PhD students each year from more than 100 applications. Applications are reviewed by a committee of faculty.

Applicants are evaluated holistically on a number of factors. A strong academic record is important, but not sufficient. A critical factor is the ability to demonstrate a research record and agenda that fit well with specific I School faculty. In a small, interdisciplinary program, it is important that applicants clearly indicate in their Statement of Purpose which faculty member(s) they are interested in researching with, and why.

To be eligible to apply to the PhD in Information Management and Systems program, applicants must meet the following requirements:

A bachelor's degree or its recognized equivalent from an accredited institution.

Superior scholastic record, normally well above a 3.0 GPA.

Indication of appropriate research goals, described in the Statement of Purpose.

For applicants whose academic work has been in a language other than English, the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS).

Not required: GRE/GMAT. Starting Fall 2021, we no longer require the GRE or GMAT. We recommend you put your time and effort towards the required application materials.

Further  information about I School Ph.D. Admissions  can be found on the I School website. 

Applying for Graduate Admission

Thank you for considering UC Berkeley for graduate study! UC Berkeley offers more than 120 graduate programs representing the breadth and depth of interdisciplinary scholarship. The Graduate Division hosts a complete list of graduate academic programs, departments, degrees offered, and application deadlines can be found on the Graduate Division website.

Prospective students must submit an online application to be considered for admission, in addition to any supplemental materials specific to the program for which they are applying. The online application and steps to take to apply can be found on the Graduate Division website .

Admission Requirements

The minimum graduate admission requirements are:

A bachelor’s degree or recognized equivalent from an accredited institution;

A satisfactory scholastic average, usually a minimum grade-point average (GPA) of 3.0 (B) on a 4.0 scale; and

Enough undergraduate training to do graduate work in your chosen field.

For a list of requirements to complete your graduate application, please see the Graduate Division’s Admissions Requirements page . It is also important to check with the program or department of interest, as they may have additional requirements specific to their program of study and degree. Department contact information can be found here .

Where to apply?

Visit the Berkeley Graduate Division application page .

Doctoral Degree Requirements

Program design.

The School of Information is an interdisciplinary school examining the design, organization, and management of information and information systems. The School of Information draws on the expertise not only of its own faculty but of the full Berkeley campus. We encourage students to take full advantage of being at this world-class University and not feel bound by disciplinary boundaries.

The PhD degree program at the School of Information is a research program. Each student is expected to work with his or her adviser to ensure that the program of study includes:

• A thorough understanding of research methods and research design.
• The ability to review current research critically.
• The ability to understand emerging trends from an interdisciplinary perspective.

Expected PhD Timeline:

• Semester 1:  Identify a faculty adviser
• Semesters 1–4:  Complete breadth courses; complete major and minor requirements
• Semester 4:  Complete the preliminary research paper
• Semester 5:  Complete preliminary exam
• Semester 6–8:  Complete qualifying exam; advance to candidacy
• Four semesters after qualifying exam:  Complete dissertation and give presentation

Please refer to  the School of Information website  for more information.

Breadth Courses

Major/Minor Areas

Related Courses

Info 201 research design and applications for data and analysis 3 units.

Terms offered: Fall 2024, Spring 2024, Fall 2023 Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry. Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences. The emphasis throughout is on making practical contributions to real decisions that organizations will and should make. Course must be taken for a letter grade to fulfill degree requirements. Research Design and Applications for Data and Analysis: Read More [+]

Hours & Format

Fall and/or spring: 15 weeks - 1.5 hours of lecture per week

Additional Format: One and one-half hours of lecture per week.

Additional Details

Subject/Course Level: Information/Graduate

Grading: Letter grade.

Research Design and Applications for Data and Analysis: Read Less [-]

INFO 202 Information Organization and Retrieval 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course introduces the intellectual foundations of information organization and retrieval: conceptual modeling, semantic representation, vocabulary and metadata design, classification, and standardization, as well as information retrieval practices, technology, and applications, including computational processes for analyzing information in both textual and non-textual formats. Information Organization and Retrieval: Read More [+]

Rules & Requirements

Prerequisites: Students should have a working knowledge of the Python programming language

Fall and/or spring: 15 weeks - 3 hours of lecture per week

Additional Format: Three hours of lecture per week.

Information Organization and Retrieval: Read Less [-]

INFO 203 Social Issues of Information 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is designed to be an introduction to the topics and issues associated with information and information technology and its role in society. Throughout the semester we will consider both the consequence and impact of technologies on social groups and on social interaction and how society defines and shapes the technologies that are produced. Students will be exposed to a broad range of applied and practical problems, theoretical issues, as well as methods used in social scientific analysis. The four sections of the course are: 1) theories of technology in society, 2) information technology in workplaces 3) automation vs. humans, and 4) networked sociability. Social Issues of Information: Read More [+]

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INFO 205 Information Law and Policy 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course uses examples from various commercial domains—retail, health, credit, entertainment, social media, and biosensing/quantified self—to explore legal and ethical issues including freedom of expression, privacy, research ethics, consumer protection, information and cybersecurity, and copyright. The class emphasizes how existing legal and policy frameworks constrain, inform, and enable the architecture, interfaces, data practices, and consumer facing policies and documentation of such offerings; and, fosters reflection on the ethical impact of information and communication technologies and the role of information professionals in legal and ethical work. Information Law and Policy: Read More [+]

Prerequisites: Consent of instructor required for nonmajors

Instructor: Mulligan

Information Law and Policy: Read Less [-]

INFO 206A Introduction to Programming and Computation 2 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course introduces the basics of computer programming that are essential for those interested in computer science, data science, and information management. Students will write their own interactive programs (in Python) to analyze data, process text, draw graphics, manipulate images, and simulate physical systems. Problem decomposition, program efficiency, and good programming style are emphasized throughout the course. Introduction to Programming and Computation: Read More [+]

Fall and/or spring: 7.5 weeks - 4 hours of lecture per week

Additional Format: Four hours of lecture per week for seven and one-half weeks.

Instructor: Farid

Introduction to Programming and Computation: Read Less [-]

INFO 206B Introduction to Data Structures and Analytics 2 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 The ability to represent, manipulate, and analyze structured data sets is foundational to the modern practice of data science. This course introduces students to the fundamentals of data structures and data analysis (in Python). Best practices for writing code are emphasized throughout the course. This course forms the second half of a sequence that begins with INFO 106. It may also be taken as a stand-alone course by any student that has sufficient Python experience. Introduction to Data Structures and Analytics: Read More [+]

Prerequisites: INFO 206A or equivalent, or permission of instructor

Credit Restrictions: Course must be completed for a letter grade to fulfill degree requirements.

Formerly known as: Information 206

Introduction to Data Structures and Analytics: Read Less [-]

INFO 213 Introduction to User Experience Design 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course will provide an introduction to the field of Human-Computer Interaction (HCI). Students will learn to apply design thinking to User Experience (UX) design, prototyping, & evaluation. The course will also cover special topic areas within HCI. Introduction to User Experience Design: Read More [+]

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INFO 214 User Experience Research 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course addresses concepts and methods of user experience research, from understanding and identifying needs, to evaluating concepts and designs, to assessing the usability of products and solutions. We emphasize methods of collecting and interpreting qualitative data about user activities, working both individually and in teams, and translating them into design decisions. Students gain hands-on practice with observation, interview, survey , focus groups, and expert review. Team activities and group work are required during class and for most assignments. Additional topics include research in enterprise, consulting, and startup organizations, lean/agile techniques, mobile research approaches, and strategies for communicating findings. User Experience Research: Read More [+]

Additional Format: Three hours of Lecture per week for 15 weeks.

User Experience Research: Read Less [-]

INFO 215 Product Design Studio 3 Units

Terms offered: Fall 2024, Fall 2023 This course will give participants hands-on digital product design experience oriented around current industry practice. The course will be project-based with an emphasis on iteration, practice, and critique. During the course, participants will work on a series of design projects through a full design process, including developing appropriate design deliverables, gathering feedback, and iterating on designs. Product Design Studio: Read More [+]

Objectives & Outcomes

Course Objectives: The course objective is to provide students interested in web and mobile Product Design with skills, practice, and experience that will prepare them for careers in product design and design-related roles.

Prerequisites: DES INV 15 or COMPSCI 160 or INFO 213 AND INFO 214; or permission of the instructor. Students can take INFO 214 and INFO 215 concurrently, but students may not drop INFO 214 and remain in INFO 215

Formerly known as: Information Systems and Management 215

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INFO 217A Human-Computer Interaction (HCI) Research 3 Units

Terms offered: Spring 2024, Fall 2021, Fall 2020 This course is a graduate-level introduction to HCI research. Students will learn to conduct original HCI research by reading and discussing research papers while collaborating on a semester-long research project. Each week the class will focus on a theme of HCI research and review foundational and cutting-edge research relevant to that theme. The class will focus on the following areas of HCI research: ubiquitous computing , social computing, critical theory, and human-AI interaction. In addition to these research topics the class will introduce common qualitative and quantitative methodologies in HCI research. Human-Computer Interaction (HCI) Research: Read More [+]

Instructor: Salehi

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INFO 218 Concepts of Information 3 Units

Terms offered: Spring 2024, Spring 2022, Spring 2020 As it's generally used, "information" is a collection of notions, rather than a single coherent concept. In this course, we'll examine conceptions of information based in information theory, philosophy, social science, economics, and history. Issues include: How compatible are these conceptions; can we talk about "information" in the abstract? What work do these various notions play in discussions of literacy, intellectual property, advertising, and the political process? And where does this leave "information studies" and "the information society"? Concepts of Information: Read More [+]

Prerequisites: Graduate standing

Instructors: Duguid, Nunberg

Concepts of Information: Read Less [-]

INFO 225 Leadership and Management 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2021 This course focuses on the practice of leadership, collaboration, and people management in contemporary, distributed, information and technology-rich organizations. Not just for potential people managers, this course is derived from the premise that a foundation in leadership, management, and collaboration is essential for individuals in all roles, at any stage of their career. To build this foundation we will take a hybrid approach, engaging literature from disciplines such as social psychology, management, and organizational behavior, as well as leveraging case studies and practical exercises. The course will place a special emphasis on understanding and reacting to social dynamics in workplace hierarchies and teams. Leadership and Management: Read More [+]

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INFO 231 Decisions and Algorithms 3 Units

Terms offered: Fall 2024, Spring 2013, Spring 2011 This class is for graduate students interested in getting an advanced understanding of judgments and decisions made with predictive algorithms. The course will survey the vast literature on the psychology of how people arrive at judgments and make decisions with the help of statistical information, focused mostly on experimental lab evidence from cognitive and social psychology. Then study the burgeoning evidence on how people use statistical algorithms in practice, exploring field evidence from a range of settings from criminal justice and healthcare to housing and labor markets. Special attention is paid to psychological principles that impact the effectiveness and fairness of algorithms deployed at scale. Decisions and Algorithms: Read More [+]

Course Objectives: Help students understand systematic human errors and explore potential algorithmic solutions.

Decisions and Algorithms: Read Less [-]

INFO 233 Social Psychology and Information Technology 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 Discusses application of social psychological theory and research to information technologies and systems; we focus on sociological social psychology, which largely focuses on group processes, networks, and interpersonal relationships. Information technologies considered include software systems used on the internet such as social networks, email, and social games, as well as specific hardware technologies such as mobile devices, computers , wearables, and virtual/augmented reality devices. We examine human communication practices, through the lens of different social psychology theories, including: symbolic interaction, identity theories, social exchange theory, status construction theory, and social networks and social structure theory. Social Psychology and Information Technology: Read More [+]

Instructor: Cheshire

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INFO 234 Information Technology Economics, Strategy, and Policy 3 Units

Terms offered: Spring 2024, Spring 2022, Spring 2021 This course applies economic tools and principles, including game theory, industrial organization, information economics, and behavioral economics, to analyze business strategies and public policy issues surrounding information technologies and IT industries. Topics include: economics of information goods, services, and platforms; economics of information and asymmetric information; economics of artificial intelligence, cybersecurity, data privacy, and peer production; strategic pricing; strategic complements and substitutes; competition and antitrust; Internet industry structure and regulation; network cascades, network formation, and network structure. Information Technology Economics, Strategy, and Policy: Read More [+]

Course Objectives: INFO234 is a graduate level course in the school's topical area of Information Economics and Policy, and can be taken by the masters and doctoral students to satisfy their respective degree requirements.

Student Learning Outcomes: Students will learn to identify, describe, and analyze business strategies and public policy issues of particular relevance to the information industry. Students will learn and apply economic tools and principles to analyze phenomena such as platform competition, social epidemics, and peer production, and current policy issues such as network neutrality and information privacy. Through integrated assignments and project work, the students will apply the theoretical concepts and analytic tools learned in lectures and readings to develop and evaluate a business model, product, or service of their choosing, e.g., a start-up idea they are pursuing.

Instructor: Chuang

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INFO 239 Technology and Delegation 3 Units

Terms offered: Fall 2021, Fall 2019, Fall 2018 The introduction of technology increasingly delegates responsibility to technical actors, often reducing traditional forms of transparency and challenging traditional methods for accountability. This course explores the interaction between technical design and values including: privacy, accessibility, fairness, and freedom of expression. We will draw on literature from design, science and technology studies, computer science, law, and ethics, as well as primary sources in policy, standards and source code. We will investigate approaches to identifying the value implications of technical designs and use methods and tools for intentionally building in values at the outset. Technology and Delegation: Read More [+]

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INFO 241 Experiments and Causal Inference 3 Units

Terms offered: Fall 2024, Spring 2024, Fall 2022 This course introduces students to experimentation in data science. Particular attention is paid to the formation of causal questions, and the design and analysis of experiments to provide answers to these questions. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology has facilitated the development of better data gathering. Experiments and Causal Inference: Read More [+]

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INFO 247 Information Visualization and Presentation 4 Units

Terms offered: Spring 2023, Spring 2022, Spring 2021 The design and presentation of digital information. Use of graphics, animation, sound, visualization software, and hypermedia in presenting information to the user. Methods of presenting complex information to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces. Course must be completed for a letter grade to fulfill degree requirements. Information Visualization and Presentation: Read More [+]

Prerequisites: INFO 206B or knowledge of programming and data structures with consent of instructor

Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of laboratory per week

Additional Format: Three hours of lecture and one hour of laboratory per week.

Instructor: Hearst

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INFO 251 Applied Machine Learning 4 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 Provides a theoretical and practical introduction to modern techniques in applied machine learning. Covers key concepts in supervised and unsupervised machine learning, including the design of machine learning experiments, algorithms for prediction and inference, optimization, and evaluation. Students will learn functional, procedural, and statistical programming techniques for working with real-world data. Applied Machine Learning: Read More [+]

Student Learning Outcomes: • Effectively design, execute, and critique experimental and non-experimental methods from statistics, machine learning, and econometrics. • Implement basic algorithms on structured and unstructured data, and evaluate the performance of these algorithms on a variety of real-world datasets. • Understand the difference between causal and non-causal relationships, and which situations and methods are appropriate for both forms of analysis. • Understand the principles, advantages, and disadvantages of different algorithms for supervised and unsupervised machine learning.

Prerequisites: INFO 206B , or equivalent course in Python programming; INFO 271B , or equivalent graduate-level course in statistics or econometrics; or permission of instructor

Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week

Additional Format: Three hours of lecture and one hour of discussion per week.

Instructor: Blumenstock

Applied Machine Learning: Read Less [-]

INFO 253A Front-End Web Architecture 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course is a survey of technologies that power the user interfaces of web applications on a variety of devices today, including desktop, mobile, and tablet devices. This course will delve into some of the core Front-End languages and frameworks (HTML/CSS/JS/React/Redux), as well as the underlying technologies enable web applications (HTTP, URI, JSON). The goal of this course is to provide an overview of the technical issues surrounding user interfaces powered by the web today, and to provide a solid and comprehensive perspective of the Web's constantly evolving landscape. Front-End Web Architecture: Read More [+]

Prerequisites: Introductory programming

Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of laboratory per week

Additional Format: Two hours of lecture and one hour of laboratory per week.

Formerly known as: Information 253

Front-End Web Architecture: Read Less [-]

INFO 253B Back-End Web Architecture 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is a survey of web technologies that are used to build back-end systems that enable rich web applications. Utilizing technologies such as Python, Flask, Docker, RDBMS/NoSQL databases, and Spark, this class aims to cover the foundational concepts that drive the web today. This class focuses on building APIs using micro-services that power everything from content management systems to data engineering pipelines that provide insights by processing large amounts of data. The goal of this course is to provide an overview of the technical issues surrounding back-end systems today, and to provide a solid and comprehensive perspective of the web's constantly evolving landscape. Back-End Web Architecture: Read More [+]

Back-End Web Architecture: Read Less [-]

INFO 255 Privacy Engineering 3 Units

Terms offered: Spring 2024, Spring 2023 The course overviews a broad number of paradigms of privacy from a technical point of view. The course is designed to assist system engineers and information systems professionals in getting familiar with the subject of privacy engineering and train them in implementing those mechanisms. In addition, the course is designed to coach those professionals to critically think about the strengths and weaknesses of the different privacy paradigms. These skills are important for cybersecurity professionals and enable them to effectively incorporate privacy-awareness in the design phase of their products. Privacy Engineering: Read More [+]

Course Objectives: Critique the strengths and weaknesses of the different privacy paradigms Describe the different technical paradigms of privacy that are applicable for systems engineering Implement such privacy paradigms, and embed them in information systems during the design process and the implementation phase Stay updated about the state of the art in the field of privacy engineering

Credit Restrictions: Students will receive no credit for INFO 255 after completing INFO 255 . A deficient grade in INFO 255 may be removed by taking INFO 255 .

Privacy Engineering: Read Less [-]

INFO 256 Applied Natural Language Processing 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2021 This course examines the use of natural language processing as a set of methods for exploring and reasoning about text as data, focusing especially on the applied side of NLP — using existing NLP methods and libraries in Python in new and creative ways. Topics include part-of-speech tagging, shallow parsing, text classification, information extraction, incorporation of lexicons and ontologies into text analysis, and question answering. Students will apply and extend existing software tools to text-processing problems. Applied Natural Language Processing: Read More [+]

Prerequisites: INFO 206A and INFO 206B or proficient programming in Python (programs of at least 200 lines of code). Proficient with basic statistics and probabilities

Instructor: Bamman

Applied Natural Language Processing: Read Less [-]

INFO 258 Data Engineering 4 Units

Terms offered: Spring 2024, Fall 2022 This course will cover the principles and practices of managing data at scale, with a focus on use cases in data analysis and machine learning. We will cover the entire life cycle of data management and science, ranging from data preparation to exploration, visualization and analysis, to machine learning and collaboration, with a focus on ensuring reliable, scalable operationalization. ensuring reliable, scalable operationalization. Data Engineering: Read More [+]

Prerequisites: INFO 206B or equivalent college-level course in computer science in Python with a C- or better AND COMPSCI C100/ DATA C100 / STAT C100 or COMPSCI 189 or INFO 251 or DATA 144 or equivalent college-level course in data science with a C- or better

Instructors: Hellerstein, Parameswaran, Jain

Data Engineering: Read Less [-]

INFO 259 Natural Language Processing 4 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course introduces students to natural language processing and exposes them to the variety of methods available for reasoning about text in computational systems. NLP is deeply interdisciplinary, drawing on both linguistics and computer science, and helps drive much contemporary work in text analysis (as used in computational social science, the digital humanities, and computational journalism). We will focus on major algorithms used in NLP for various applications (part-of-speech tagging, parsing, coreference resolution, machine translation) and on the linguistic phenomena those algorithms attempt to model. Students will implement algorithms and create linguistically annotated data on which those algorithms depend. Natural Language Processing: Read More [+]

Prerequisites: Familiarity with data structures, algorithms, linear algebra, and probability

Natural Language Processing: Read Less [-]

INFO C262 Theory and Practice of Tangible User Interfaces 4 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 This course explores the theory and practice of Tangible User Interfaces, a new approach to Human Computer Interaction that focuses on the physical interaction with computational media. The topics covered in the course include theoretical framework, design examples, enabling technologies, and evaluation of Tangible User Interfaces. Students will design and develop experimental Tangible User Interfaces using physical computing prototyping tools and write a final project report. Theory and Practice of Tangible User Interfaces: Read More [+]

Instructor: Ryokai

Also listed as: NWMEDIA C262

Theory and Practice of Tangible User Interfaces: Read Less [-]

INFO C265 Interface Aesthetics 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This course will cover new interface metaphors beyond desktops (e.g., for mobile devices, computationally enhanced environments, tangible user interfaces) but will also cover visual design basics (e.g., color, layout, typography, iconography) so that we have systematic and critical understanding of aesthetically engaging interfaces. Students will get a hands-on learning experience on these topics through course projects, design critiques , and discussions, in addition to lectures and readings. Interface Aesthetics: Read More [+]

Also listed as: NWMEDIA C265

Interface Aesthetics: Read Less [-]

INFO 271B Quantitative Research Methods for Information Systems and Management 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Introduction to many different types of quantitative research methods, with an emphasis on linking quantitative statistical techniques to real-world research methods. Introductory and intermediate topics include: defining research problems, theory testing, casual inference, probability, and univariate statistics. Research design and methodology topics include: primary/secondary survey data analysis, experimental designs, and coding qualitative data for quantitative analysis. Quantitative Research Methods for Information Systems and Management: Read More [+]

Prerequisites: Introductory statistics recommended

Quantitative Research Methods for Information Systems and Management: Read Less [-]

INFO 272 Qualitative Research Methods for Information Systems and Management 3 Units

Terms offered: Fall 2024, Fall 2023, Fall 2022 Theory and practice of naturalistic inquiry. Grounded theory. Ethnographic methods including interviews, focus groups, naturalistic observation. Case studies. Analysis of qualitative data. Issues of validity and generalizability in qualitative research. Qualitative Research Methods for Information Systems and Management: Read More [+]

Instructor: Burrell

Qualitative Research Methods for Information Systems and Management: Read Less [-]

INFO 283 Information and Communications Technology for Development 3 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 This seminar reviews current literature and debates regarding Information and Communication Technologies and Development (ICTD). This is an interdisciplinary and practice-oriented field that draws on insights from economics, sociology, engineering, computer science, management, public health, etc. Information and Communications Technology for Development: Read More [+]

Fall and/or spring: 15 weeks - 3 hours of seminar per week

Additional Format: Three hours of seminar per week.

Instructor: Saxenian

Formerly known as: Information C283

Information and Communications Technology for Development: Read Less [-]

INFO 288 Big Data and Development 3 Units

Terms offered: Spring 2024, Spring 2021, Spring 2019 As new sources of digital data proliferate in developing economies, there is the exciting possibility that such data could be used to benefit the world’s poor. Through a careful reading of recent research and through hands-on analysis of large-scale datasets, this course introduces students to the opportunities and challenges for data-intensive approaches to international development. Students should be prepared to dissect, discuss, and replicate academic publications from several fields including development economics, machine learning, information science, and computational social science. Students will also conduct original statistical and computational analysis of real-world data. Big Data and Development: Read More [+]

Prerequisites: Students are expected to have prior graduate training in machine learning, econometrics, or a related field

Big Data and Development: Read Less [-]

INFO 289 Public Interest Cybersecurity: The Citizen Clinic Practicum 3 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 This course provides students with real-world experience assisting politically vulnerable organizations and persons around the world to develop and implement sound cybersecurity practices. In the classroom, students study basic theories and practices of digital security, intricacies of protecting largely under-resourced organizations, and tools needed to manage risk in complex political, sociological, legal, and ethical contexts. In the clinic , students work in teams supervised by Clinic staff to provide direct cybersecurity assistance to civil society organizations. We emphasize pragmatic, workable solutions that take into account the unique needs of each partner organization. Public Interest Cybersecurity: The Citizen Clinic Practicum: Read More [+]

Repeat rules: Course may be repeated for credit with instructor consent.

Public Interest Cybersecurity: The Citizen Clinic Practicum: Read Less [-]

INFO 290 Special Topics in Information 1 - 4 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]

Repeat rules: Course may be repeated for credit when topic changes. Students may enroll in multiple sections of this course within the same semester.

Fall and/or spring: 8 weeks - 2-8 hours of lecture per week 15 weeks - 1-4 hours of lecture per week

Summer: 10 weeks - 1.5-6 hours of lecture per week

Additional Format: One to four hours of lecture per week. One and one-half to six hours of lecture per week for 10 weeks. Two to eight hours of lecture per week for 8 weeks.

Special Topics in Information: Read Less [-]

INFO 290M Special Topics in Management 1 - 4 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Management: Read More [+]

Additional Format: One to four hours of lecture per week. Two to eight hours of lecture per week for 8 weeks.

Special Topics in Management: Read Less [-]

INFO 290S Special Topics in Social Science and Policy 2 - 4 Units

Terms offered: Fall 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Social Science and Policy: Read More [+]

Fall and/or spring: 8 weeks - 4-8 hours of lecture per week 15 weeks - 2-4 hours of lecture per week

Additional Format: Two to four hours of lecture per week. Four to eight hours of lecture per week for 8 weeks.

Special Topics in Social Science and Policy: Read Less [-]

INFO 290T Special Topics in Technology 2 - 4 Units

Terms offered: Spring 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Technology: Read More [+]

Special Topics in Technology: Read Less [-]

INFO 291 Special Topics in Information 1 - 4 Units

Terms offered: Prior to 2007 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]

Repeat rules: Course may be repeated for credit when topic changes.

Fall and/or spring: 15 weeks - 1-4 hours of lecture per week

Additional Format: One to four hours of lecture per week.

Grading: Offered for satisfactory/unsatisfactory grade only.

Instructor: Hoofnagle

INFO 293 Information Management Practicum 0.5 Units

Terms offered: Fall 2016, Summer 2016 10 Week Session, Spring 2016 This course is designed to help School of Information graduate students maximize their internship, practicum, or independent research experiences. Information Management Practicum: Read More [+]

Course Objectives: Experience the practical application of your academic knowledge to real-world professional contexts; Gain insight into an organization and how one might make a valuable contribution; Reflect on the information the experience has provided, to see if it fits within one’s personal value set and work/life manifestos. Try out various professional activities to see when you are in ‘flow’;

Student Learning Outcomes: Assess the organizational culture of a company, governmental body, or non-governmental organization Connect academic knowledge about information management to real-world professional contexts Evaluate the effectiveness of a variety of information science techniques when deployed in organizational situations Integrate the student's own individual professional goals with the organization's needs relevant to the internship or practicum Reflect critically on the internship or practicum experience

Prerequisites: Consent of a Head Graduate Adviser for the School of Information

Repeat rules: Course may be repeated for credit without restriction.

Fall and/or spring: 15 weeks - 1 hour of internship per week

Summer: 10 weeks - 1.5 hours of internship per week

Additional Format: One hour of internship per week. One and one-half hours of internship per week for 10 weeks.

Information Management Practicum: Read Less [-]

INFO 294 Doctoral Research and Theory Workshop 2 Units

Terms offered: Spring 2024, Spring 2023, Spring 2022 An intensive weekly discussion of current and ongoing research by Ph.D. students with a research interest in issues of information (social, legal, technical, theoretical, etc.). Our goal is to focus on critiquing research problems, theories, and methodologies from multiple perspectives so that we can produce high-quality, publishable work in the interdisciplinary area of information research. Circulated material may include dissertation chapters , qualifying papers, article drafts, and/or new project ideas. We want to have critical and productive discussion, but above all else we want to make our work better: more interesting, more accessible, more rigorous, more theoretically grounded, and more like the stuff we enjoy reading. Doctoral Research and Theory Workshop: Read More [+]

Prerequisites: PhD students only

Fall and/or spring: 15 weeks - 2 hours of workshop per week

Additional Format: Two hours of workshop per week.

Doctoral Research and Theory Workshop: Read Less [-]

INFO 295 Doctoral Colloquium 1 Unit

Terms offered: Fall 2024, Fall 2023, Spring 2023 Colloquia, discussion and readings designed to introduce students to the range of interests of the school. Doctoral Colloquium: Read More [+]

Prerequisites: Ph.D. standing in the School of Information

Fall and/or spring: 15 weeks - 1 hour of colloquium per week

Additional Format: One hour of colloquium per week.

Doctoral Colloquium: Read Less [-]

INFO 296A Seminar 2 - 4 Units

Terms offered: Fall 2024, Spring 2024, Fall 2023 Topics in information management and systems and related fields. Specific topics vary from year to year. Seminar: Read More [+]

Prerequisites: Consent of instructor

Fall and/or spring: 15 weeks - 2-4 hours of seminar per week

Additional Format: Two to Four hours of Seminar per week for 15 weeks.

Seminar: Read Less [-]

INFO 298 Directed Group Study 1 - 4 Units

Terms offered: Fall 2019, Spring 2016, Fall 2015 Group projects on special topics in information management and systems. Directed Group Study: Read More [+]

Credit Restrictions: Students will receive no credit for INFO 298 after completing INFOSYS 298.

Fall and/or spring: 15 weeks - 1-4 hours of directed group study per week

Summer: 8 weeks - 1.5-7.5 hours of directed group study per week

Additional Format: One to four hours of directed group study per week. One and one-half to seven and one-half hours of directed group study per week for 8 weeks.

Directed Group Study: Read Less [-]

INFO 298A Directed Group Work on Final Project 1 - 4 Units

Terms offered: Spring 2022, Spring 2016, Spring 2015 The final project is designed to integrate the skills and concepts learned during the Information School Master's program and helps prepare students to compete in the job market. It provides experience in formulating and carrying out a sustained, coherent, and significant course of work resulting in a tangible work product; in project management, in presenting work in both written and oral form; and, when appropriate, in working in a multidisciplinary team. Projects may take the form of research papers or professionally-oriented applied work. Directed Group Work on Final Project: Read More [+]

Prerequisites: Consent of instructor. Course must be taken for a letter grade to fulfill degree requirements

Additional Format: One to four hours of directed group study per week.

Directed Group Work on Final Project: Read Less [-]

INFO 299 Individual Study 1 - 12 Units

Terms offered: Fall 2023, Summer 2016 8 Week Session, Spring 2016 Individual study of topics in information management and systems under faculty supervision. Individual Study: Read More [+]

Fall and/or spring: 15 weeks - 1-12 hours of independent study per week

Summer: 8 weeks - 2-22.5 hours of independent study per week

Additional Format: Format varies.

Individual Study: Read Less [-]

INFO 375 Teaching Assistance Practicum 2 Units

Terms offered: Spring 2024, Fall 2021, Fall 2020 Discussion, reading, preparation, and practical experience under faculty supervision in the teaching of specific topics within information management and systems. Does not count toward a degree. Teaching Assistance Practicum: Read More [+]

Fall and/or spring: 15 weeks - 2 hours of lecture per week

Additional Format: Two hours of lecture per week.

Subject/Course Level: Information/Professional course for teachers or prospective teachers

Instructor: Duguid

Teaching Assistance Practicum: Read Less [-]

INFO 602 Individual Study for Doctoral Students 1 - 5 Units

Terms offered: Spring 2016, Fall 2015, Spring 2015 Individual study in consultation with the major field adviser, intended to provide an opportunity for qualified students to prepare themselves for the various examinations required of candidates for the Ph.D. degree. Individual Study for Doctoral Students: Read More [+]

Fall and/or spring: 15 weeks - 1-5 hours of independent study per week

Additional Format: One to Five hour of Independent study per week for 15 weeks.

Subject/Course Level: Information/Graduate examination preparation

Individual Study for Doctoral Students: Read Less [-]

Contact Information

School of information.

102 South Hall

Phone: 510-642-1464

Senior Director of Student Affairs

Siu Yung Wong

[email protected]

Senior Director of Admissions

Julia Sprague

[email protected]

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Information Science

Doctor of philosophy, university at buffalo.

• Delivery Mode 100% Online
• Total Credits 72
• Degree Level Doctor of Philosophy
• Contact Us 716-645-2939

Earn your doctorate degree online

You will earn the same diploma as our on-campus students.

Are you interested in exploring research questions in information science? Are you considering moving into a faculty position in the field? Do you want to enhance your leadership experience in libraries? If you answer yes to any of these questions, our doctoral program in information science is your ticket to the next phase of your career. 

A PhD in information science will give you the opportunity to develop sophisticated quantitative and qualitative research skills to equip you to delve into the complex information problems facing humanity and contemporary organizations. As human interaction and cultural expression continue to be facilitated digitally, the workings of digital technologies, their impact and their uses need to be understood. Our doctoral degree in information science will provide the opportunity to study these issues in depth. 

The information field is changing rapidly, and offering myriad opportunities for future scholars of information science.

What's it like to earn this degree online?

Let's put your mind at ease about online learning.

• 100% Online This program is presented 100% online. You will not be expected to attend any classes on campus.
• Live classes You will learn in real-time while the instructor leads the class. Courses are similar to in-person classes, but you participate online.
• Classes on your schedule Courses are semester based and classwork can be completed around your work and family commitments. There is no set time where you are required to log in to attend class.
• Same faculty as on-campus The faculty that teach online classes are the same faculty that students learn from on-campus.
• Learn by doing Participate in field experiences such as internships, clinical placements, and service learning to apply your academic knowledge in the world.
• Credit for prior knowledge Get college credit for experience that you have already gained at school or in the workforce.
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• Programs : PhD in Information Studies

PhD in Information Studies

alt="Doctoral PhD students collaborating in the Information eXeprience Lab"

Where Grand Challenges Meet Interdisciplinary Solutions

We live in the Information Age, offering unprecedented opportunities but also unmatched threats and challenges. Information systems and technologies are fundamentally shaping the behaviors of individuals, organizations, and society. To understand the dynamics of our world, and to help shape a future that reflects social values, research at the School of Information crosses disciplinary divides, bridges the arts and the sciences, and applies human insights to technological advances.

Our flexible curriculum and immersive mentorship with  world-class faculty who are experts in their fields prepare students to become high-quality, high-impact researchers, scholars, and teachers. Throughout the doctoral program, students will learn to reason and evaluate ideas and data across disciplines, see beyond current approaches to problems, and cross disciplinary boundaries in search of answers to the grand challenges facing today's modern information society.

Join Our Community of Innovative Scholars

At the School of Information, you will work with faculty who are among the best in the world in their areas of expertise. You will be immersed in an environment that offers the facilities and resources of one of the premier research universities in the US, and live in a city that is both a rapidly growing center for IT research and development and one of the country's most vibrant cities in which to live and work.

Admissions & Funding

Learn about admissions procedures as well as funding available for doctoral students.

Program Overview

Our curriculum offers flexibility to tailor your coursework and explore research interests.

Meet Our Faculty

Over 20 full-time, world-class faculty come from diverse, interdisciplinary backgrounds.

Research at the iSchool

We're tackling the greatest challenges facing today's modern information society — how to understand the extraordinary complexity of information, to discover principles and processes for managing its massive scale, and exploring ways to leverage it to enhance our lives.

PhD Degree Requirements

• Committees & Annual Review
• Coursework & Plan of Study
• Qualifying Procedure
• Proposal & Dissertation Defense

What Do We Look For?

The study of information extends beyond any existing field. Our PhD students come from a wide range of disciplinary backgrounds, and we welcome applications from interested candidates regardless of the field of study in which you completed your prior degree(s). A master's degree is not required to apply. 

We seek the best and brightest people who thrive on challenges:

People dedicated to creating new forms of information systems that can augment human and organizational capabilities.

People committed to exploring the human and technological principles and processes that underlie information complexity.

People energized by a vision of a diverse society where access to relevant information is not a luxury, but a requirement.

People appreciative of the importance and challenge of preserving and disseminating information on the human cultural record.

If you want to join us in helping to forge a better information society:  Apply to the PhD Program

Our Vision & Values

The School of Information is committed to making a positive difference in people’s lives through excellence in research, teaching, and public engagement. Our core values underpin our efforts to shape the field of information for human and social benefit.

About The University of Texas at Austin

The University of Texas at Austin is one of the largest public universities in the US. Beyond our top-ranked international graduate program, UT Austin is one of the world's premier research universities and is located in one of the sunniest and most vibrant cities in which to live and work: Austin, TX.

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PhD in Information

Phd in information, unleash your research prowess and shape the future of information as you work with top data and information science faculty..

Find out how the UArizona PhD is the right program for you:

Academic Units Required

Next Application Deadline

Full Funding Available for Qualified Students

The University of Arizona PhD in Information prepares students to excel as researchers and thought leaders in academia, government and industry.

Offered on campus, the PhD in Information is typically completed in five years , requiring 54 units for primary work plus 9-15 units for the PhD minor.

The School of Information is committed to creating an inclusive intellectual space for all, irrespective of background or characteristics, and we seek a wide range of students with diverse research interests and experiences , including machine learning, natural language processing, artificial intelligence, virtual/mixed reality, game development, immersive technologies, new media and internet studies, human-computer interaction, digital curation, archival studies and the future of work.

As the state's only member of the iSchools consortium , we foster interdisciplinary understanding, preparing students for  advanced information and data careers as professors, scientists, consultants, directors and more.

"The PhD in Information at the University of Arizona offers the perfect union of history, mathematics, programming, causal inference, formalizing language, teaching and logic." Salena Torres Ashton, PhD in Information '25

ADMISSIONS & FUNDING

The annual application deadline for all students is:

• Fall 2024: January 20, 2024

The iSchool successfully supports all PhD students in securing funding, including full tuition plus a stipend for living expenses, through at least four years of the program.

CURRICULUM & DEGREE REQUIREMENTS

Offered on campus, the PhD in Information consists of:

• 36 credits of major coursework
• 9 to 15 credits of minor coursework
• 18 dissertation credits

The program includes research methods, graduate seminars, directed research, elective courses, dissertation research, comprehensive exams and dissertation proposal and defense.

RESEARCH AT THE iSCHOOL

Our faculty and PhD students are engaged in research around all aspects of the information sciences without regard for disciplinary boundaries.

RESEARCH AREAS

• Information collections, libraries, databases, archives and ethics
• Machine learning, artificial intelligence and algorithmic thinking
• Applied natural language processing
• Virtual reality, video game design and human-computer interaction
• Biological informatics
• Data science, social network analysis and computational social science
• Social science and internet studies
• Internet of things

Learn More and View Faculty

RESEARCH CENTERS & LABS

• Center for Digital Society and Data Studies
• Biosemantics Research Group
• Computational Language Understanding Laboratory
• Digital Storytelling and Oral History Laboratory
• Extended Reality and Games Laboratory
• Machine Learning and Artificial Intelligence Laboratory
• Metadata Analytics Laboratory
• The co/lab: Critical Archives and Curation Collaborative

Learn More and View Centers & Labs

CAREER OUTCOMES

Our innovative, interdisciplinary doctoral program prepares students for positions in research-intensive institutions in academic, corporate, nonprofit and governmental fields.

ISCHOOL PHD STUDENTS

The PhD in Information hosts a diverse mix of interdisciplinary, research-focused students who come from across the U.S. and around the world to study information science at Arizona's iSchool.

Are you ready to shape the future of information?

Learn more about the PhD in Information by contacting us at [email protected] or begin your application today:

Start Your Application

Ph.D. Programs in Library and Information Sciences

Written by Kelly Davis

MLIS – Clarion University | Youth Services Librarian

A Ph.D. in library science or information science provides scholars with the tools to produce individual research, collaborate with other researchers, and teach library and information science in higher education. The standards are not as concrete for Ph.D. programs as for Master of Library and Information Science (MLIS) programs, but there are a few ways to rank a program’s quality. One way is to look at the school of information offering the Ph.D. and the other programs they offer, including if the school provides an MLIS degree and if the degree is accredited by the American Library Association. Another sign of a quality program is seeing the research and progress made by graduates and faculty and how much access a Ph.D. student will have to quality research opportunities.  

In this article, we highlight some of the most comprehensive Ph.D. programs in the U.S. based on these two significant factors. We also try to provide a few programs in each region of the U.S. in the hopes that one of the programs will be near you. Additionally, we will look at many other aspects of each program as well, including the format, what the coursework involves, and how to apply and become qualified for each Ph.D. program in library and information science. 

All of the following Ph.D. programs come from a school that is accredited by the American Library Association and offers students the ability to work with decorated and world-class scholars and professors. Additionally, the programs we chose are in areas that provide ample career opportunities following the program. If you want to know more about each program and what may be a good fit for you, keep exploring below.

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Liberty University

Online D.B.A. in Information Systems

Experience real-world applications, equipping you as an innovator in strategy, security, ethics, design and development, and business process support.

Ph.D. in Information from the University of Michigan

Doctoral students will work one on one with professors in information, many of which specialize in communication technologies, collective research capabilities, and how to change social relations. All professors know a wide range of research and topics and look at information and how individuals and communities interact with information and technology. Additionally, in your application, you will pick which professors you want to work with out of the 100 in the program. 

Many Ph.D. graduates receive careers as professors at prestigious schools including Brown University, Stanford University, and the National University of Singapore. Many receive fellowships at prestigious universities including Harvard University and Brown University. Other careers they received shortly after graduating include UX researcher for Google, Yahoo, and Facebook, design researcher for IBM, and data analysis for Microsoft. 

How to apply

First, apply online and pay the application fee. Send in a Statement of Purpose essay which will include the area of research you want to contribute to and past research done. Additionally, you will need to send in a personal history statement, a resume, three letters of recommendation, and transcripts. Your admission acceptance will be multifaceted in the factors the program will examine. Namely, they will look at past research, work experience, and your goals moving forward. 

Ph.D. in Information Studies at Long Island University

The Ph.D. program includes a dissertation and requires 60 credit hours. There are two areas of study for students which are Information Access and Systems, and Information Studies and Services. Additionally, this program can be taken part-time or full-time to accommodate students’ schedules. The on-campus classes can be taken between 6 PM and 9 PM. It is also the only program of its kind in the Metropolitan New York area, and it is within a school that is accredited by the American Library Association. 

How to Apply

You need a master’s degree to qualify, which can be in any area of study. Admissions will also evaluate you based on previous research, work experience, and the interest you have in research going forward. Then apply online , and pay the application fee. You will also need to send in transcripts, three letters of recommendation,  a statement of research and area of study, a resume, a personal statement, and a sample of scholarly writing. 

Ph.D. in Information Science and Technology at Syracuse University

Syracuse University offers its Ph.D. scholars opportunities to work and research one on one with professors and other doctoral students. The research opportunities are in areas of philosophy, psychology, sociology, computers and digital information, policy studies, librarianship, and information communication. This program is not offered online or part-time. It is a four to five-year program of full-time residential coursework. The Ph.D. student is funded by the school, and for this reason, the program is very selective. 

Apply online , pay the application fee, and send in transcripts and any other research or work experience completed. Applicants will be evaluated by a committee based on their readiness for the program, their intellectual ability and academic record, research interests as they relate to faculty interests, communication skills, and research preparedness. 

Ph.D. Philosophy in Information and Library Science at the University of North Carolina at Chapel Hill 

Chapel Hill is the most respected information science department in North Carolina and its MLIS program is often ranked first or second by the U.S. News and World Reports. Their doctoral program is sure to hold to the same standards. Many of the faculty for the MLIS program are also professors in the doctoral program. The difference is that Ph.D. students work one on one with these world-class professors. The program is rigorous, but it provides some flexibility for those holding a job, or have families to care for. There is financial support for Ph.D. students and many receive full support for the first four to five years of the program; typically, students finish within that period. Students learn more about library and information science and they enhance their research and presentation of research capability. 

How to apply 

Accepted students in this program are often seeking to be information leaders, have a knowledge of diverse research methods, enjoy being an independent investigator, are committed to finding information to address critical questions, and enjoy intellectual challenges.  Applicants must have either an MLIS degree or an equivalent of study and research completed. To apply, go online and fill out the online application and pay the application fee. Also, send in all transcripts, an updated resume, three letters of recommendation, and a statement of purpose that includes your area of research interest. 

Ph.D. in Communication and Information at Kent State University

The Ph.D. program in communication and information from Kent State University in Ohio is part of the information science school, which has been around for over sixty years. The program is offered online and in person and is a 70-credit hour degree program including a dissertation. Doctoral students must also pass the doctoral comprehensive examination to graduate. 

The degree program is for those interested in research, information communication, teaching higher education and academic librarianship administration, and administration in other information fields. The school of information science provides and encourages outreach opportunities for those pursuing a degree in library and information science. The outreach programs give students more experience and knowledge in conducting scholarly research and analyzing the needs of communities and the diversity within those communities. 

How to Apply 

To qualify you must have a master’s degree and a minimum of a 3.30 GPA on a 4.0 scale. Then applicants must fill out an online application and pay the application fee. Applicants should also send in official transcripts, an updated resume, a goal statement, a sample of scholarly writing, and three letters of recommendation.

Gateway Ph.D. in Library and Information Science at San Jose State University

San Jose, California is a great place to earn a doctoral degree in librarianship and information science because of the various research options and a number of opportunities due to the variety of ethnic groups and cultures in the cities of California. The Gateway doctoral degree program in library and information science teaches students to become independent scholars as well as collaborate with other researchers and colleagues.  Ph.D. students complete the program mostly online, however, there is an annual meeting that is a week-long and focuses on collaborative research. San Jose’s Gateway program also holds a partnership with the Manchester Metropolitan University, which offers doctoral students the opportunity to work with their professors as well in their research and to learn from them in coursework. With this program, students from both schools have won prestigious awards for their individual and collaborative research. 

The application process is one of the more extensive doctoral programs, and the program is highly selective. There are three stages of the application process. The first is filling out an online application , paying an application fee, and sending in a statement of purpose, an updated resume of related work, unofficial transcripts, two letters of recommendation, and a 1000-word research proposal. In the second stage, the applicant is interviewed by faculty members, and they may ask for more writing samples. If the applicant makes it past the first two stages, then Manchester Metropolitan University will go over the final applicants and approve or disapprove of them. 

Doctorate in Information Science at the University of Washington

The information science department at the University of Washington is known for the research their doctoral students and their faculty do. They also teach students to become professors in their field and to be administrators in librarianship. The doctoral program puts emphasis on collaboration between students and faculty, plus they care about diversity in ethnicity and culture with the idea it brings richer research due to a mix of different backgrounds. The Ph.D. students also learn about UX, or User experience, which is how to evaluate a culture or group and its relationship with information and technology. Doctoral students are also taught to use various research methods and various ways to present information and research results. 

To qualify for the doctoral program, applicants must have a bachelor’s degree with an average 3.0 GPA on a 4.0 scale, and a master’s or other additional higher education degree is preferred. However, admissions also look at your experience, interest and goals, and scholarly research.  Applicants can apply online . You will need to pay the application fee, send in transcripts, a personal statement, a diversity statement, a research statement, three letters of recommendation, and your interest in areas of research and which faculty member(s) you prefer to work with.

Ph.D. in Library and Information Science at Simmons University

Simmons University is located in Boston Massacutes which provides an ideal environment for research and study. Boston is full of history, diversity, and cutting-edge technology. The area also has a multitude of career opportunities after graduation. This degree program provides a flexible format for those who do not live in the area because the courses can be taken online. Additionally, students can take a mix of courses online and in person. The main focus of the degree program is to further skills in research and teaching within the library and information science.  Doctoral students also gain skills in organizing, analyzing, retrieving, and managing information. Students also learn how to preserve materials and learn more about archiving physical documents and digitizing documents for online archives. Simmons University also partners with other universities in other countries for higher quality and diversity of research. 

To qualify for the program, applicants need either an MLIS degree or an MS degree in Library and Information Science from a program accredited by the American Library Association. To apply, go online and fill out the application and pay the application fee. Also, submit all transcripts from any colleges or universities you attended, and send in a statement of purpose, three letters of recommendation, a writing sample of previous research, and a comprehensive curriculum vitae. 

University of Texas at Austin Ph.D. in Information Studies

The University of Texas at Austin has a well-funded Ph.D. program in information studies that allow for new technology to be a part of the curriculum and research. The doctoral students also can learn and then teach other institutions about various new technologies and the best ways to implement them to meet their community’s needs. Additionally, Austin is an advancing and thriving city in the midst of technological growth, and the city offers opportunities for research and careers in information science. The program includes a dissertation and 39 hours of coursework. During this time, students will produce two peer-reviewed scholarly journals. 

You do not have to have a master’s degree to qualify for this program, but you do need a bachelor’s degree and an average 3.0 GPA on a 4.0 grading scale. 

Then, apply online and pay the application fee. Afterward, send in three letters of recommendation, and a statement of purpose. 

The University of North Texas’ Information Science Ph.D. Program

The Doctoral program at the University of North Texas is the nation’s largest Ph.D. program in the Information Science discipline. It is also interdisciplinary so that students can work with students and faculty in various other degree programs including geography, computer science, engineering, linguistics, and merchandising. The program also has concentration options and dual degrees in data science consumer behavior and experience management, journalism cybersecurity, geospatial information systems, health informatics, and linguistics.

To qualify for any doctoral program you must have at least a 3.50 in either your undergraduate degree or your master’s degree. Also, talk to the admissions department for the information science department. Then apply online , send in transcripts, pay the application fee, and send any other documents or scholarly writing the application requests. 

Florida State University PH.D. in Information

Florida is a great state to earn a Ph.D. in library and information because of the diversity in the state of Florida as well as the environmental and marine biology research that is done in Florida. This is good for research opportunities as well as career opportunities. The number of good colleges in FLordia provides many career opportunities as well. 

Florida State has a program called the iSchool and it is ALA-accredited. Additionally, their doctoral students are able to travel across the U.S. for presenting at conferences like the ALA conference, ACM CHI Conference on Human Factors in Computing Systems, and the Association for Information Science and Technology conference.

To qualify you must have a master’s degree and at least a 3.0 GPA. To apply, fill out the online application and send in a resume, statement of purpose, writing sample, and three letters of recommendation. Right now the GRE requirement is waived. Be sure to speak to an admissions counselor for any additional application requirements or recommendations. 

Library and Information Science Ph.D. Programs Final Thoughts

Ph.D. programs in library and information science are worth pursuing if you have a passion for sharing information through various modes to communicate with other scholars, but more importantly, with the world and its many communities. Many of these programs are lengthy and require dedication, but if you believe you have the drive to become a Ph.D. in Information and Library Science, then I hope this article helps you find a good match for your professional research and career goals. 

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Search results (15)

PhD Candidate in Program Verification

Employment 1.0 FTEGross monthly salary € 2,770 - € 3,539Required background Research University DegreeOrganizational unit Faculty of ScienceApplication deadline 20 June 2024Do you want to carry out a PhD in program verification and proof assistant...

Three 2-year Postdoctoral Fellowships at the Zukunftskolleg

(Fulltime, E 13 TV-L)Reference No: 2024/114. The preferred start date is April 1st, 2025. Conditionally on the submission of an external grant, the position can be extended for an additional year. In principle, the position can be divided into two...

PhD student on the subject of collaborative AI (m/v/x)

PhD student on the subject of collaborative AI (m/v/x)Are you inspired by building human-centric, explainable, and collaborative AI? There is a vacancy for a 4-year PhD position in the Intelligent and Autonomous Systems research group at Centrum W...

PhD positions in Sustainable Data-centric Control

Description:Multiple PhD positions are available in the Mathematical Engineering Department at the University of Louvain, Belgium in the context of a newly-started research project. The goal of the project is to develop learning and control tools ...

PhD Scholarship Autonomous Mobility

1 - Working at the VUBFor more than 50 years, the Vrije Universiteit Brussel has stood for freedom, equality and solidarity, and this is very much alive on our campuses among students and staff alike.  At the VUB, you will find a diverse collectio...

Doctoral student in underwater communication and signal processing

Project descriptionThird-cycle subject: Information and Communication TechnologyThe Nord Stream incident has demonstrated the vulnerability of critical underwater infrastructure, such as gas pipeli...

PhD Student in Trustworthy Autonomous Systems and Explainable Artificial Intelligence

Deadline: 16.07.2024The University of Applied Sciences and Arts of Southern Switzerland (SUPSI) has opened a full time (100%) position for a PhD student in Trustworthy Autonomous Systems and Explainable Artificial Intelligence at the Department of...

Doctoral student in Informatics

Reference number ORU 2.1.1-03449/2024Örebro University and the School of Business are looking for a doctoral student for the doctoral programme in Informatics, concluding with a doctoral degree.Start date: 15 October 2024.Project descriptionThe Di...

PhD Research Fellows in ICT - Machine Learning and Security

About the positionThree 100% positions are available at the University of Agder, Faculty of Engineering and Science as PhD Research Fellows in machine learning, affiliated to the Department of Information and Communication Technology, for a period...

PhD on Realizing the first European Health Data Space focused on Prevention

Are you passionate about pioneering research at the intersection of health technology, data exchange, and ethical considerations? Join us at the Information Systems group of Eindhoven University of Technology and be part of an exciting project fun...

PhD student AI-driven innovation management

BackgroundNew developments in artificial intelligence (AI) have a profound impact on the business world and how companies organize themselves. Within this doctoral project, the aim is to investigat...

PhD Research Fellow in Information Systems

About the positionA fix-term 100 % position is available at the University of Agder, Faculty of Social Sciences as a PhD Research Fellow in Information Systems, affiliated to the Department of Information Systems, for a period of three years. The ...

Research Associate (Doctoral Student) (m/f/x) in Entrepreneurship and Family Enterprise

(100%, TV-L E13)TUM School of Management at TUM Campus Heilbronn invites applications for a Research Associate (m/f/x) at the level of TV-L E13 (public sector pay scale) at the newly founded Global Center for Family Enterprise (Prof. Dr. Miriam Bi...

Two PhD Research Fellow in Information Systems

PhD Candidate in Software and System Verification

About the SnTSnT is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in Luxembourg by fueling innova...

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Best Master’s in Data Science for 2024

It’s no secret that the need for data experts is growing due to the exponential amount of data being generated every day. One of the best ways to gain the in-demand skills to be able to harness, analyze, and create value from data is pursuing a master’s degree. This ranking was last updated February 2024.

UC Berkeley’s Master’s in Data Science — Online

Syracuse University MS in Applied Data Science Online

1. Harvard University

• ACCEPTANCE RATE, 2023-24
• AVERAGE UNDERGRADUATE GPA, 2023-24 ENROLLEES
• FALL TERM ENROLLMENT, 2022–23
• GRADUATION RATE, 2022-23
• NUMBER OF APPLICANTS IN 2023-24
• ONE-YEAR RETENTION RATE, 2022-23

2. University of North Texas

3. New York University

Earn Your Master’s in Data Science Online From SMU

4. University of Michigan–Ann Arbor

5. Carnegie Mellon University

6. University of California–Irvine

7. University of Rochester

8. Indiana University–Bloomington

Maryville University Master of Science in Data Science | Online

9. University of Arizona

10. University of Delaware

11. Appalachian State University

12. University of Minnesota

13. Oklahoma State University

14. University of Missouri

15. Georgia State University

16. Maryville University

17. University of Michigan–Dearborn

18. New York Institute of Technology

19. University of San Francisco

20. DePaul University

21. Marquette University

22. Willamette University

23. Rochester Institute of Technology

24. Texas Tech University

25. Worcester Polytechnic Institute

26. University of St. Thomas

27. American University

28. University of Maryland

29. CUNY Graduate Center

Frequently Asked Questions

Data science is one of the fastest growing fields—job openings are expected to grow by 35% by 2023, according to the U.S. Bureau of Labor Statistics . And students graduating with a master’s in data science often land six figure salaries. The reason it’s a fast growing field, with high paying jobs, is because companies across all industries want data-savvy professionals in this era of digitization. Data provides companies and organizations with the resources they need to make better decisions—and in turn, they need professionals with data science skills who know how to understand and analyze data. 

The GPA you’ll need to get accepted into a master’s program for data science varies by school. For all of the programs ranked by Fortune for 2024, the average undergraduate GPA for enrollees was 3.27. Students at Harvard and New York University had the highest GPA, with 3.87 and 3.75, respectively. Marquette University enrollees had the lowest reported GPA—at 3.01.

Master’s degree programs in data science can be offered in person, online or in a hybrid format—and that might be the difference in what the “best program” for you means. Fortune ranks the top five in-person programs for 2024 as: Harvard University, the University of North Texas, New York University, University of Michigan—Ann Arbor, and Carnegie Mellon University. Additionally, our ranking of the top five online programs in 2023 include: University of Southern California, UC—Berkeley, Bay Path University, New Jersey Institute of Technology, and Clemson University.

On average, it takes about one-and-a-half to two years to complete a master’s degree program in data science—with most programs requiring roughly anywhere from 25 to 60 credits to graduate. So it does depend on each individual program and whether you choose to be a full-time or part-time student. That said, thanks to a boost in salary and expanded career options, many students find it worthwhile to obtain a master’s degree in data science—and Gen Z considers the role of data scientist to be one of the most satisfying occupations .

A master’s degree in data science will teach you how to understand and analyze data. But because it’s a recently defined career path, how it’s applied can vary significantly. As Maurizio Porfiri, a New York University professor, told Fortune: “It’s a weird thing because it’s very vague. I discovered after a while that I had become a data scientist : people just started to refer to me as such.” But sometimes the first step to finding your place in the world of data science is picking a specialization—what type of problem you want to solve by using data. And a master’s degree can either help you find that specialization, or if you’ve already got the answer, will teach you the skills to pursue it.

Fortune compiled a list of seven universities that offer free online data science courses , which offers prospective students an opportunity to learn more about this field. Each university—Harvard University, the University of Michigan, UC Irvine, John Hopkins University, Columbia University, MIT, and Duke University—offers a different course, from linear regression to data science ethics to data science in real life. However, the common goal of these free courses is to give people an inside look into the field.

In 2022, data scientists earned median salaries of $103,500, according to the U.S. Bureau of Labor Statistics . But a degree from a top program might mean even more money; New York University’s (ranked third on Fortune’s best in-person data science programs) 2022-23 graduates with a master’s in data science earned an average salary of $143,000 four months after graduation, according to data provided by the university.

• Warsaw University of Technology
• Posted on: 17 June 2024

PhD Student Position within the project “Development of Functional Three-Dimensional Bone Metastasis Model with Tissue Engineering Approach"

Job information, offer description.

Warsaw University of Technology (WUT) is not only the oldest, but also the best technical university in Poland. The Faculty of Materials Science and Engineering (FMSE) of the WUT   is a leading research and teaching centre in the field of materials science and engineering in Poland.

The project will be realized in BioMaterials Group (bio.materials.pl) – one of the FMSE subgroups – which brings together 20 early stage and experienced researchers focused on the biomaterial science and development of novel technologies for tissue engineering, implants, and drug delivery systems.

BioMaterials Group is offering a PhD position in the area of biofabrication of in vitro 3D bone metastasis model.

PhD position is available within the project “Development of Functional Three-Dimensional Bone Metastasis Model with Tissue Engineering Approach”, BonMetFun, in collaboration with University of Zurich, funded by Polish National Science Center.

The overall objective of the project is to establish an ex vivo bone metastasis model that is based on avascularized and functionally perfused engineered bone organoid (bone marrow and bone) that allows to investigate the pathophysiology of cancer metastasis, the interplay with blood mononuclear cells (PBMC) to mimic the blood environment and serves as a model for functional testing.

PhD student will be involved in bio-inks optimization for bio-printing purposes, designing and biofabrication of 3D bone organoids with special emphasis on bone and bone marrow part characterization. Evaluation of experimental data, optimization of co-culture conditions and data analysis will be the responsibilities of a PhD student.

Where to apply

Requirements.

The ideal candidate will have master's degree in Materials Science Bioengineering, Chemical Engineering, or related disciplines, obtained not earlier than 1 year before the engagement in the project is required. Experience in hydrogel synthesis, material characterization and 3D bioprinting is essential. High motivation and strong interest in research is required. The candidate should have an innate ability for solution-orientated problem solving; strong interest in cell-biomaterial interactions and bone tissue engineering. The experience in cell handling will be considered as a benefit.

Additional Information

• 4-year PhD study finished with PhD diploma in Materials Science
• Stipend of about 50 000 PLN per year, with possible increase after midterm evaluation
• Engagement into an ambitious research and possibility to build the academic career
• Excellent support for research and facilities for professional and personal development

Applications, assembled as single PDF files, should contain a complete resume, a cover letter describing research interests and goals, a full list of publications and copies of up to three relevant scientific papers, as well as the names and contact information of three references (expected to provide letters of recommendation). Applications should be sent to [email protected] , using the subject line “BonMetFun PhD”

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• Computer Science, MS

Gain cutting-edge expertise with our Master of Science in Computer Science (MSCS). Through flexible electives aligned with your career goals, or two optional areas of specialization in data science or software engineering, the MSCS prepares you to excel in today’s fiercely competitive tech industry.

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About this Program

Computer science degree in seattle’s global tech industry.

Seattle University's Master of Science in Computer Science (MSCS) program offers a curriculum based on theoretical foundations and practical applications. The curriculum includes advanced courses in core areas of computer science and flexible electives that align with your professional goals.

History-Making Program for Today’s Computer Science Leaders

Seattle University has long been a leader in computer science and software engineering education. We established our pioneering Master of Software Engineering program in 1979 and awarded the world's first MSE degree in 1982. Our curriculum has been shaped by close contact with local industry professionals, ensuring that courses are relevant to the workplace and that projects are tailored to the professional needs of our students.

As the Puget Sound region developed into one of the world's leading technology hubs, our faculty developed connections with industry leaders to ensure SU students remain competitive in the job market.  Today, computer science is the fastest-growing program on our campus, and our graduate students are employed by major tech brands such as Microsoft, Meta, Google and others.

• How to Apply

Graduate Computer Science Degree at a Glance

Learn more about how this graduate degree from the Department of Computer Science will contribute to your career goals. Below you can explore the program variants and decide which path is the best fit for you. See for yourself how impactful a Seattle University degree can be.

In the general option, you get to choose your electives. You can develop a focused or broad foundation that aligns with your interests and academic goals. There are two variations of the MSCS general option:

• Course Only: You take an additional elective course and a seminar that explores state-of-the-art technology advances in computer science.
• Research Project: You complete a faculty-supervised research project spanning 2-3 academic quarters. The research projects enable you to focus on your specific areas of interest and the research interests of faculty members.

If you chose to participate in research project opportunities, you’ll have a chance to be mentored by faculty, publish your work, and present on campus or at conferences. These projects provide distinctive opportunities to gain hands-on research experience and prepare you for career advancement or for further post-graduate education at internationally recognized institutions.

Sample Plan for MSCS – General Option

The MSCS with a specialization in data science (MSCS-DS) provides you the opportunity to develop computer solutions related to data science. Our unique program is designed so that upon completion, you’ll receive both an MSCS degree and a specialization within data science.

This combination is very attractive to today's leading employers as there's growing demand for developers that have experience in data science. As a student in this specialization, you must complete the set of core courses that are part of all MSCS degrees at Seattle University, plus a set of data science courses. The program culminates in a capstone project that addresses real-world challenges in the field of data science.

The specialization can be completed in as little as five academic quarters, only if you start in the fall quarter. Due to course sequencing, if you start in the winter quarter you can complete the program in seven academic quarters, and if you start in the spring quarter you can complete the program in six academic quarters.

Data Science Specialization Outcomes

• Demonstrate a solid foundation in core areas of data science theory and practice including data analysis methodologies, machine learning, and best practice in data visualization and presentation of analysis results and conclusions.
• Demonstrate theoretical and practical skills in the systems and software engineering needed to process large data sets.

Sample Plan for MSCS - Data Science Specialization

The MSCS with a specialization in software engineering (MSCS-SE) enables you to build the skill set you will need for a fulfilling career in the software industry. You'll gain hands-on experience across the software development life cycle — from requirements analysis, to architecture and design, to development and testing. The Department of Computer Science has been working with local tech companies for decades, meaning you'll benefit from close industry connections and a curriculum that is current and relevant to industry needs.

The MSCS-SE program consists of a set of core courses common to all MSCS degrees at Seattle University plus a set of software engineering courses. The program culminates in a capstone project that addresses real-world challenges in the field of software engineering.

The specialization can be completed in six academic quarters if you start in the fall quarter, five academic quarters if you start in the winter quarter and seven academic quarters if you start in spring quarter.

Software Engineering Specialization Outcomes

• Demonstrate a solid foundation in core areas of software engineering theory and practice including all areas of the software development life cycle.
• An ability to function effectively on teams to establish goals, plan tasks, meet deadlines, manage risk and produce deliverables.

Sample Plan for MSCS - Software Engineering Specialization

• Demonstrate in-depth knowledge of core areas and advanced topics in computer science.
• An ability to design, implement and evaluate computer-based solutions to meet a given set of requirements.
• An ability to effectively communicate technical concepts in written and oral form.
• An ability to make informed judgments in computing practice based on legal, ethical and social considerations.
• An ability to understand computer science literature to maintain professional currency.

What You’ll Learn

Explore the classes you’ll take as a student here.

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Top 25% in Science & Engineering

Seattle University ranks #40 in the nation —U.S. News & World Report, 2023

Ready for Seattle’s Top Tech Jobs

High-Demand Graduates

Our curriculum was developed in collaboration with industry leaders and designed to prepare you with the industry’s most in-demand technical and problem-solving skills, enabling you to distinguish yourself in a fiercely competitive job market. In fact, most MSCS graduates are employed within six months of graduation (2017–2020). Seattle University graduates are employed by Amazon, Microsoft, Google, F5 Networks and other major tech firms in the region.

Projected Job Growth (2022-2032)

According the the Bureau of Labor Statistics, demand for software developers is expected to grow 25 percent over the next decade.

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As a student at Seattle University, you'll have the opportunity to learn in one of the largest and most culturally diverse independent universities in the Northwest. Our Jesuit values mean we see the world through a global, justice-focused lens. Our strong commitment to diversity and low student-to-faculty ratio help create a forward-thinking, close-knit community where everyone can feel at home—and go on to thrive in a global workforce.

Support for Career Changers

Are you interested in the MSCS program but have no undergraduate computer science coursework? Bridge to the MSCS through the Computer Science Fundamentals Certificate. You’ll get the coursework you need to transition to the full computer science graduate program.

From Our Alumni

Rupansh phutela.

“The CS faculty at Seattle U is truly exceptional, combining deep expertise with a genuine commitment to student engagement and growth. Working closely with some of the best professors at the university, Dr. Shadrokh Samavi and Prof. Timothy Spinney, I witnessed an unwavering dedication to student success and willingness to provide guidance and mentorship. If you're looking to advance your education in computer science and explore cutting-edge technology stacks, I highly recommend Seattle U.”

MSCS ’23

Featured Faculty

Professor and Amazon Chair, Computer Science

Professor, Computer Science

Assistant Professor, Computer Science

Assistant Teaching Professor

Professor and Associate Chair, Computer Science

Associate Professor, Computer Science

Associate Teaching Professor, Computer Science

Associate Teaching Professor, Computer Science Director, Computer Science Fundamentals Certificate Program

Adjunct, Computer Science

Professor and Director of MSCS Ph.D., Computer Science, University of Cincinnati

Discover More Programs to Explore

Computer science fundamentals, certificate.

The Computer Science Fundamentals Certificate prepares you for a new career in the tech industry and is a bridge to the MS in Computer Science program. No prior programming experience is required.

• Certificate

Data Science, MS

Our graduate degree in data science combines aspects of statistics and computer science with data analysis and modeling. You’ll gain the technical and analytical skills needed to advance your career.

• Master of Science

Computer Science, Accelerated BS & MS

Earn both a BS and MS in computer science in only 5 years. You’ll save time on your advanced degree and enjoy a streamlined graduate application process.

• Bachelor of Science, Master of Science

Get in Touch

We’re here to help. For information about computer science graduate degrees at Seattle University, contact:

Computer Science Department

• [email protected]
• 206-296-5510

Library and Information Science Certificate

Specialized certificate to advance in your career.

Enhance your employment opportunities and empower yourself with the skills and knowledge in focused specialization.

Advance in your career with confidence and expert knowledge.

Beginning Fall 2024, the MLIS Program will offer job-oriented certificates to provide skills-based training for BA/BS degree holders. This post-baccalaureate certificate program supports library workers and others who want to advance their knowledge and skills in specialized areas, but don't choose to pursue a master's degree. 

The Library and Information Science Certificate program has two certificate options available:

Foundations of LIS Certificate

Custom Certificate. This certificate option allows students to take courses based on their interest in a designated focus. Custom certificate options include academic libraries, archives, digital libraries, public libraries, managing school libraries, teaching in school libraries, and technology integration in school libraries.

Format: Online; synchronous and asynchronous

Start: Fall, Spring, or Summer

Time to completion: up to 24 months

Credits required: 12

Tuition per credit (2024–2025): TBD

Total tuition: TBD

Rates are subject to change each June 1. Tuition and fee information

Scholarship Opportunities

A St. Catherine University education is one of the most worthwhile investments you’ll ever make, and we are committed to helping you find ways to make that investment affordable.

Library and Information Science Certificate students employed by a St. Kate's corporate or community partner may be eligible for a 10% tuition reduction .

Graduate students may also be eligible for loan and grant programs .

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Discover a supportive community invested in more than your academic success — we help you connect with your purpose. Our goal is to help each of our students develop the knowledge and empowerment to transcend what they thought was possible.

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• School of Computer Science
• GRADUATE ASSISTANT (GA) & TEACHING ASSISTANT (TA) POSITIONS NOW AVAILABLE FOR THE FALL 2024 TERM!

GRADUATE ASSISTANT (GA) & TEACHING ASSISTANT (TA) POSITIONS NOW AVAILABLE FOR THE FALL 2024 TERM!

SCHOOL OF COMPUTER SCIENCE

APPLICATION DEADLINE DATE:  SUNDAY, JUNE 23, 2024

HOW TO APPLY

Fill out the online application (link at bottom of page) and upload the required documents.

All positions and hours are subject to sufficient enrolment and budgetary approval.  In accordance with Article 12:01 of the CUPE 4580 Collective Agreemen t, the School of Computer Science invites applications for Graduate Assistantship (GA) and Teaching Assistantship (TA) positions for the FALL 2024 term.

GA/TA employees are expected to make themselves available to report for all assigned duties, both in-person and on-campus. Most classes across the University are held face-to-face on campus or have a face-to-face component. Refer to the University’s current health and safety regulations .

Some positions are open to both GA’s and TA’s however GA applicants are given priority.

Each position can be comprised of a combination of any of the listed courses as needed.  Most courses are a 12-week duration (September 3, 2024, to December 31, 2024).

Assistants cannot commence their GA/TA duties until email confirmation of the approval of their contract is received from Human Resources (email titled "Authorization to Commence GA/TA Duties").

ELIGIBILITY REQUIREMENT

Successful applicants must be available to attend at the specified time of the course/lab/exams and to report for all assigned duties, which include both in-person and on-campus duties.

GA and TA appointments will be offered to qualified applicants in accordance with the criteria specified in Article 12:03 (for GA’s) and 12:04 (for TA’s) of the CUPE 4580 Collective Agreement.

DUTIES AND EXPECTATIONS

Must have excellent communication skills.

Must have critical thinking and problem-solving skills.

Must be punctual and reliable.

Ability to meet deadlines.

Complete assigned tasks on time.

ESSENTIAL QUALIFICATIONS

Successful applicants must meet all essential qualifications:

Successful completion of the course (80% minimum average) or demonstrated experience/knowledge in the subject matter (which will be determined by interview).

Must have a minimum cumulative average of 75%.

Must have a minimum major average of 80%.

Brightspace/Microsoft Teams experience: must be familiar with Brightspace and MS Teams or be able to acquire knowledge through training.

GA applicants must be registered full-time in a Computer Science graduate program (MSc or PhD).

Remote internet access requirements: must have access to a computer with a reliable internet connection with video and audio capabilities.

PREFERRED REQUIREMENTS/SKILLS FOR THE SCHOOL OF COMPUTER SCIENCE

Preferred qualifications will only be considered if there are 2 or more qualified applicants who meet the ‘required’ essential qualifications AND who are relatively equal based on the GA/TA criteria as per articles 12:03 (for GA’s) or 12:04 (for TA’s) of the CUPE 4580 collective agreement.

Preference for TA positions will be given to applicants registered in a Computer Science undergraduate program.

Completion of CTL GA/TA Academy workshop(s) is an asset.

Center for Teaching and Learning (CTL) Brightspace Training completed.

NOTE 1 – GRADUATE STUDENT INFORMATION

• GA appointments cannot exceed 140 hours total for the Fall 2024 term period of September 3,2024 to December 31, 2024.Refer to Articles 12, 13, and 14 of the CUPE 4580 Collective Agreement for eligibility details.
• Phase I Information:  Graduate students must MAINTAIN FULL TIME REGISTRATION throughout the term and must be in good standing in the degree program to hold a GA position.  Students who meet the Phase I tuition refund deadline for the FALL 2024 term are therefore NOT eligible to hold a GA in the same term.  See Faculty of Graduate Studies Important Dates .
• Graduate assistants MUST APPLY EACH TERM by the application deadline, in accordance with Article 13:  “With respect to those students who have applied for and been accepted for Assistantships, the Assistant will not be paid for any shortfall of hours at the end of their respective program, provided the University has satisfied its obligation to post available positions each term in writing and on the AAU website and to offer the minimum terms of support in accordance with Article 13:01 (a) & (b) and provided that the Assistant has applied in writing or via email by the application deadline for each term until they have received the minimum terms of support in accordance with Article 13:01 (a) & (b)”.

NOTE 2 – MAC GRADUATE STUDENT INFORMATION

• The Master of Applied Computing Program (MAC) is NOT an eligible program to support GA funded positions.  Consequently, applicants registered in the MAC program will not be eligible for consideration.

NOTE 3 – UNDERGRADUATE INFORMATION

• The total number of hours of a TA appointment will depend on the number of applications received and is anticipated to be from 50 to 100 hours total per semester. Note that Teaching Assistants cannot be employed for more than 100 TA hours total per semester as per Article 14 of the CUPE 4580 Collective Agreement.  If you already hold or have applied for another TA position (in this or another department), note that the total combined hours for all TA appointments held in all departments cannot exceed 100 hours for the FALL 2024 term period from September 6, 2024, to December 31, 2024.
• Undergraduate students must be registered throughout the term and must be in good standing in the degree program to hold a TA position.
• International undergraduate students must be registered full-time and be in good standing to hold a TA position.

In pursuit of the University of Windsor’s Employment Equity Plan, members for the designated groups (Women, Aboriginal Peoples, Visible Minorities, Persons with Disabilities, and Members of Sexual Minorities) are encouraged to apply.

If you have any questions on any the above, please contact Monique Ritz, the School of Computer Science Graduate Secretary at:  [email protected]

PROJECTED POSITIONS AND HOURS FOR FALL 2024 TERM

COMP 1000-1-2-30 KEY CONCEPTS IN COMPUTER SCIENCE

REQUIRED SKILLS : STRONG MATHEMATICAL BACKGROUND

19 GA/TA positions projected – 2,637 hours

COMP 1047-30-91 COMPUTER CONCEPTS - END USERS

7 GA/TA positions projected – 1,036 hours

COMP 1400-1-2-30 INTRO: ALGORITHMS & PROGRAMMING I

REQUIRED SKILLS: MASTERY OF ALGORITHMS & PROGRAMMING; ADVANCED KNOWLEDGE OF C PROGRAMMING LANGUAGE

12 GA/TA positions projected – 1,727 hours

COMP 1410-1-2 INTRO: ALGORITHMS & PROGRAMMING II

REQUIRED SKILLS: MASTERY OF ALGORITHMS & PROGRAMMING

5 GA/TA positions projected – 676 hours

COMP 2057-91 INTRODUCTION TO THE INTERNET

REQUIRED SKILLS: INTERNET PROTOCOLS, SERVICES & DATA TRANSMISSION; HTML & CSS LANGUAGES; WEBSITE DEVELOPMENT & DESIGN; ACCESSIBILITY & SECURITY FEATURES OF WEBSITES; HOW WEB BROWSERS & SEARCH ENGINES WORK; INTERNET LANGUAGES, TECHNOLOGIES & APPLICATIONS IN GENERAL

5 GA/TA positions projected – 700 hours

COMP 2067-95 PROGRAMMING FOR BEGINNERS

REQUIRED SKILL : SKILLED WITH PYTHON; FAMILIARITY OF COMPUTERS IN UNIVERSITY LABS; ABLE TO WORK AS AN INSTRUCTOR OR A GA/TA LEAD.

6 GA/TA positions projected – 840 hours

COMP 2087-95 PROGRAMMING FOR BEGINNERS II

REQUIRED SKILLS:  PROFICIENT IN PYTHON PROGRAMMING; ABILITY TO EXPLAIN PROGRAMMING CONCEPTS TO STUDENTS

2 GA/TA positions projected – 187 hours

COMP 2097-91 SOCIAL MEDIA MARKETING FOR END USERS

REQUIRED SKILLS : KNOWLEDGE OF SOCIAL MEDIA & DATA ANALYTICS RECOMMENDED.

COMP 2120-1-2 OBJECT-ORIENTED PROGRAMMING USING JAVA

REQUIRED SKILLS : EXPERIENCE IN JAVA PROGRAMMING; STRONG UNDERSTANDING OF OBJECT-ORIENTED PRINCIPALS; ABILITY TO WORK WITH VERSION CONTROL SYSTEMS (PREFERABLY IN GIT)

13 GA/TA positions projected – 1,727 hours

COMP 2310-1 THEORETICAL FOUNDATIONS: COMPUTER SCIENCE

REQUIRED SKILLS: ABLE TO DO RIGOROUS PROOFS IN MATHEMATICAL LOGIC & SET THEORY

COMP 2540-1-2 DATA STRUCTURES & ALGORITHMS

TA REQUIRED SKILLS:   EXPERIENCE IN T/A & MENTORING; DEEP KNOWLEDGE OF PROGRAMMING LANGUAGES (JAVA, C++, PYTHON)

GA REQUIRED SKILLS: ALGORITHMS & DATA STRUCTURES; LEADERSHIP & MENTORING

12 GA/TA positions projected – 1,563 hours

COMP 2547-1 APPLIED ALGORITHMS/DATA STRUCTURES

REQUIRED SKILLS:   THOROUGH UNDERSTANDING OF DATA STRUCTURES & ALGORITHMS (FORMAL NOTION OF ALGORITHMS; BASICS OF TIME & SPACE COMPLEXITY; LINEAR DATA STRUCTURES SUCH AS STACKS, QUEUES, LINKED LISTS); NONLINEAR DATA STRUCTURES (TREES, BINARY TREES); RECURSION; SORTING TECHNIQUES (HEAP SORT, QUICK SORT, MERGE SORT); SEARCHING TECHNIQUES (BINARY SEARCH, BINARY SEARCH TREES, HASHING); ALGORITHM DESIGN PARADIGMS (DIVIDE-AND-CONQUER,  GREEDY ALGORITHMS).

PRACTICAL APPLICATION & EXAMPLES: REAL-WORLD EXAMPLES: USING RELATABLE EXAMPLES TO DEMONSTRATE PRACTICAL APPLICATIONS OF DATA STRUCTURES & ALGORITHMS.

PROGRAMMING FUNDAMENTALS: UNDERSTANDING PSEUDOCODE: ABILITY TO UNDERSTAND & USE PSEUDOCODE TO CREATE ALGORITHMS.

PROGRAMMING LANGUAGES: BASIC UNDERSTANDING OF PROGRAMMING LANGUAGES (PYTHON, JAVA, OR C++)

1 GA/TA positions projected – 140 hours

COMP 2560-1-2 SYSTEM PROGRAMMING

REQUIRED SKILLS: PROFICIENT IN C LANGUAGE; MUST HAVE WORKED/STUDIED IN UNIX/LINUX ENVIRONMENT; MUST HAVE TAKEN SIMILAR COURSES IN SYSTEM PROGRAMMING USING C LANGUAGE UNDER UNIX/LINUX ENVIRONMENT

10 GA/TA positions projected – 1,353 hours

COMP 2650-1 COMPUTER ARCHITECTURE I - DIGITAL DESIGN

REQUIRED SKILLS:   EXPERIENCE IN C PROGRAMMING LANGUAGE

9 GA/TA positions projected – 1,190 hours

COMP 2660-1 COMP ARCHITECTURE II: MICRO - PROGRAMMING

REQUIRED SKILLS : ABILITY TO INSTRUCT LABS AND MANAGE LARGE CLASSES AND LECTURES

7 GA/TA positions projected – 887 hours

COMP 2707-91 ADVANCED WEBSITE DESIGN

REQUIRED SKILLS: WEBSITE DESIGN & DEVELOPMENT IN GENERAL; CREATING WEB PAGES WITH HTML, CSS, JAVASCRIPT, JQUERY & PHP (IMPORTANT LANGUAGES); FORMS ON WEB PAGES (CREATION, VALIDATION, ETC.); DESIGNING FOR MULTIPLE SCREEN RESOLUTIONS BY BUILDING A RESPONSIVE WEB PAGE DESIGN FOR DESKTOPS, TABLETS & SMARTPHONES

3 GA/TA positions projected – 373 hours

COMP 2750-1 SELECTED TOPICS I

REQUIRED SKILLS : FAMILIAR WITH PROGRAMMING COMPETITIONS; EXPERIENCE IN C, C++ & JAVA

COMP 3037-95 INFORMATION SECURITY FOR IT

REQUIRED SKILLS: HAVE TAKEN AT LEAST 1 INFORMATION SECURITY RELATED COURSE WITH FINAL GRADE OVER 85%; HAVE TAKEN OPERATING SYSTEMS COURSE

COMP 3057-91 CYBER-ETHICS

REQUIRED SKILLS : BACKGROUND IN ETHICS

2 GA/TA positions projected – 280 hours

COMP 3110-1 INTRO TO SOFTWARE ENGINEERING

REQUIRED SKILLS: EXPERIENCE IN MOBILE/WEB DEVELOPMENT; DATABASE KNOWLEDGE; ABILITY TO WORK WITH VERSION CONTROL SYSTEMS (PREFERABLY IN GIT)

5GA/TA positions projected - 700 hours

COMP 3150-1 DATABASE MANAGEMENT SYSTEMS

REQUIRED SKILLS : SQL LANGUAGE SKILLS; PL/SQL LANGUAGE SKILLS; PROFICIENCY IN PROGRAMMING DATABASE QUERYING FRONT ENDS WITH LANGUAGES LIKE PHP, JAVA ETC.

COMP 3220-95 OBJECT-ORIENTED SOFTWARE ANALYSIS/DESIGN

REQUIRED SKILLS : EXPERIENCE WITH SOFTWARE PROJECT DESIGN DOCUMENTS, DEVELOPING WITHIN & MANAGING LARGE CODE BASES; EXPERIENCE WRITING SOFTWARE IN A TEAM/GROUP; EXPERIENCE WITH SOFTWARE DESIGN PATTERNS IE: IMPLEMENTATION EXPERIENCE (IDEALLY BOTH DIRECTLY & FROM REQUIREMENT/SPECIFICATION DOCUMENTS; REFACTORING EXPERIENCE)

COMP 3500-1 INTRO TO MULTIMEDIA SYSTEMS

REQUIRED SKILLS: FAMILIAR WITH PHOTOSHOP/GIMP, USE OF 2D ANIMATION CONCEPTS/APPLICATION PACKAGE; KNOWLEDGE ABOUT MULTIMEDIA CONCEPTS

COMP 3540-1 THEORY OF COMPUTATION

REQUIRED SKILLS: STRONG MATHEMATICAL BACKGROUND

4 GA/TA positions projected – 560 hours

COMP 3670-1 COMPUTER NETWORKS

REQUIRED SKILLS: THOROUGH UNDERSTANDING OF OSI MODEL; ANALYZE NETWORK TRAFFIC USING WIRESHARK; IP CONFIGURATION & BASIC NETWORK TROUBLESHOOTING

4 GA/TA positions projected - 560 hours

COMP 4150-1 ADVANCED & PRACTICAL DATABASE SYSTEMS

REQUIRED SKILLS : MUST HAVE TAKEN COMP 3150; SQL LANGUAGE SKILLS; PL/SQL LANGUAGE SKILLS; PROFICIENCY IN PROGRAMMING DATABASE QUERYING FRONT ENDS WITH LANGUAGES LIKE PHP, JAVA ETC.

3 GA/TA positions projected - 327 hours

COMP 4220-1 AGILE SOFTWARE DEVELOPMENT

REQUIRED SKILLS: AGILE SOFTWARE DEVELOPMENT WITH SCRUM & TEST-DRIVEN DEVELOPMENT; SQL & C# PROGRAMMING LANGUAGE; DEVELOPMENT OF DESTOP APPS WITH VISUAL STUDIO

2 GA/TA positions projected – 233 hours

COMP 4250-1 BIG DATA ANALYTICS/DATABASE DESIGN

REQUIRED SKILLS: DATA MINING; MACHINE LEARNING; DATABASE

2 GA/TA positions projected – 240 hours

COMP 4400-1 PRINCIPLE OF PROGRAMMING LANGUAGES

REQUIRED SKILLS: LOGIC & LOGIC PROGRAMMING; HIGHER ORDER FUNCTIONS & FUNCTIONAL PROGRAMMING; CONCURRENT PROGRAMMING

COMP 4540-1 DESIGN & ANALYSIS OF COMP ALGORITHMS

REQUIRED SKILLS: HAVE TAKEN A PROOF-BASED, AS OPPOSED TO INTUITION-BASED, COURSE IN THE DESIGN & ANALYSIS OF ALGORITHMS

2 GA/TA positions projected – 240 hours

COMP 4670-1 NETWORK SECURITY

REQUIRED SKILLS: FAMILIAR WITH PROGRAMMING/SCRIPTING LANGUAGES; UNDERSTANDING OF NETWORKING FUNDAMENTALS (PROTOCOLS, TOPOLOGIES, DEVICES); KNOWLEDGE OF OPERATING SYSTEMS AND VIRTUAL MACHINES

COMP 4730-1 ADVANCED TOPICS: AI I

REQUIRED SKILLS: THOROUGH KNOWLEDGE IN MATH (ANALYSIS & PROBABILITY) & ALGORITHMS

1 GA/TA positions projected – 93 hours

COMP 8117-1-2-3 ADVANCED SOFTWARE ENGINEERING TOPICS

REQUIRED SKILLS: DEEP TECHNICAL KNOWLEDGE (SOFTWARE & COMPUTER ARCHITECTURES), BUSINESS KNOWLEDGE (ORGANIZATIONAL STRUCTURES) OR SCIENTIFIC/GENERAL KNOWLEDGE; AUTONOMY & FLEXIBILITY; PROACTIVE, SELF-STARTER, CONTRIBUTION TO BUILD COURSE MATERIAL

COMP 8157-1-2 ADVANCED DATABASE TOPICS

REQUIRED SKILLS : SQL, PL/SQL; WORKING KNOWLEDGE OF ANY NON-RELATIONAL DATABASES LIKE MONGODB; DATA MINING

COMP 8207-1 EMERGING PARADIGMS IN COMPUTING TECHNOLOGIES

COMP 8347-1-2-3 INTERNET APPLICATION/DISTRIBUTED SYSTEMS

REQUIRED SKILLS : DJANGO (MOST IMPORTANT); HOW TO DEVELOP WEBSITES USING DJANGO. PYTHON LANGUAGE, USING IDE’S SUCH AS PYCHARM OR VSCODE.

COMP 8547-1-2-3 ADVANCED COMPUTING CONCEPTS

REQUIRED SKILLS : STRONG UNDERSTANDING OF DATA STRUCTURES & ALGORITHMS: LINEAR DATA STRUCTURES: IN-DEPTH KNOWLEDGE OF STACKS, QUEUES, & LINKED LISTS. NON-LINEAR DATA STRUCTURES: UNDERSTANDING TREES, BINARY TREES, & MORE ADVANCED STRUCTURES SUCH AS AVL TREES, RED-BLACK TREES & SPLAY TREES. RECURSION: PROFICIENCY IN EXPLAINING & DEMONSTRATING RECURSION TECHNIQUES & APPLICATIONS. DYNAMIC PROGRAMMING: UNDERSTANDING OF DYNAMIC PROGRAMMING CONCEPTS & ABILITY TO EXPLAIN HOW TO SOLVE PROBLEMS USING THIS APPROACH.

SORTING TECHNIQUES : KNOWLEDGE OF VARIOUS SORTING ALGORITHMS INCLUDING HEAP SORT, QUICK SORT, & MERGE SORT. SEARCHING TECHNIQUES: FAMILIARITY WITH BINARY SEARCH, BINARY SEARCH TREES, & HASHING. TIME & SPACE COMPLEXITY: ABILITY TO ANALYZE & EXPLAIN THE COMPLEXITY OF ALGORITHMS. ALGORITHM DESIGN PARADIGMS: KNOWLEDGE OF DIVIDE-AND-CONQUER, GREEDY ALGORITHMS, DYNAMIC PROGRAMMING & BACKTRACKING. FORMAL NOTION OF ALGORITHMS: UNDERSTANDING THE FORMAL DEFINITIONS & PROPERTIES OF ALGORITHMS.

PROGRAMMING PROFICIENCY: PROFICIENCY IN JAVA: ABILITY TO TEACH & ASSIST STUDENTS WITH JAVA PROGRAMMING. UNDERSTANDING OF WEB CRAWLING WITH SELENIUM: ABILITY TO TEACH THE BASICS OF WEB CRAWLING USING SELENIUM, PROVIDING PRACTICAL EXAMPLES & APPLICATIONS.

PRACTICAL APPLICATION & EXAMPLES: REAL-WORLD EXAMPLES: USING RELATABLE EXAMPLES TO DEMONSTRATE THE PRACTICAL APPLICATIONS OF DATA STRUCTURES & ALGORITHMS.

COMP 8567-1-2 ADVANCED SYSTEMS PROGRAMMING

3 GA/TA positions projected – 326 hours

COMP 8677-1-2-3 NETWORKING & DATA SECURITY

REQUIRED SKILLS : HAVE TAKEN COMPUTER NETWORK COURSE WITH AT LEAST AN 85%; HAVE TAKEN 1 INFORMATION SECURITY COURSE

COMP 8967-1 INTERNSHIP PROJECT I

REQUIRED SKILLS: PROJECT MANAGEMENT; SOFTWARE ENGINEERING; LEADERSHIP; KNOWLEDGE OF SOFTWARE DEVELOPMENT & MANAGEMENT

8 GA/TA positions projected – 1,027 hours

APPLICATION LINK:  SCHOOL OF COMPUTER SCIENCE ONLINE GA/TA APPLICATION

— Published on Jun 12th, 2024