University of Michigan

What you'll study

This PhD programme is research-led and flexible, combining advanced coursework with an extended period of independent research leading to a doctoral dissertation. Students take graduate-level courses across core computer science and information science areas, then focus on a specialised research topic under the supervision of a faculty advisor.

• Core topics and typical modules: advanced algorithms, machine learning and statistical learning theory, databases and data management, information retrieval, networked systems and security, human–computer interaction, natural language processing, computational social science, and the ethics and policy of information technologies.
• Programme structure: an initial phase of coursework to build foundations and breadth, qualifying or preliminary examinations to demonstrate readiness for research, a proposal/qualifying project in the chosen research area, and a sustained dissertation research and defence. Many students also complete teaching or mentoring assignments as part of their professional development.
• Research training: emphasis on experimental design, reproducible empirical methods, theoretical analysis where appropriate, and scholarly communication. Students are expected to publish in peer-reviewed conferences and journals and to present work at seminars and workshops.
• Interdisciplinary opportunities: students can collaborate across the School of Information, the College of Engineering, and units such as the Michigan Institute for Data Science (MIDAS) and AI research groups. Projects often involve partnerships with industry labs, healthcare, public policy, or social science departments.

Entry requirements

Admission is competitive and based on research potential as well as academic preparation. Typical requirements include:

• Academic degree: a good bachelor’s degree in computer science, information science, engineering, mathematics or a related discipline; many successful applicants hold a relevant master’s degree.
• Academic record: strong performance in relevant undergraduate/graduate coursework such as algorithms, probability and statistics, programming, and systems or data courses.
• Research experience: demonstrated research ability or potential, shown through a master’s thesis, publications, research projects, internships, or close collaboration with faculty.
• Supporting documents: a research statement outlining intended areas of study and potential faculty collaborators, an academic CV, transcripts, and letters of recommendation from persons able to assess research aptitude.
• English language: evidence of proficiency for applicants whose first language is not English, as specified by the university’s admissions policy.

Career prospects

Graduates of this PhD programme pursue a range of research-focused and leadership roles. Common career paths include:

• Academic positions: tenure-track faculty roles or postdoctoral research positions at universities worldwide.
• Industry research: researcher or research scientist roles in corporate labs and R&D groups (for example in AI, systems or human-centred computing teams).
• Technical leadership and engineering: senior engineering, architecture, or data science roles that require deep technical expertise and the ability to lead complex projects.
• Start-ups and entrepreneurship: founding or joining technology start-ups where advanced research and specialised knowledge provide competitive advantage.
• Public sector and policy roles: technical advisor or research positions in government, non-profits and think tanks working at the intersection of technology, privacy, and public policy.

Why study at University of Michigan

The University of Michigan offers a strong environment for doctoral research in computer and information sciences, combining leading faculty, diverse research centres and a broad collaborative ecosystem. Students benefit from interdisciplinary collaboration across the School of Information, the Department of Computer Science and Engineering, and campus-wide initiatives in data science and AI.

Located in Ann Arbor, the university provides access to extensive computing resources, cross-disciplinary seminars, and connections with a large alumni network and regional industry. The department supports doctoral students with mentoring, funding packages for research and teaching, and professional development to prepare graduates for research careers in academia and industry.