University of California

What you'll study

The programme centres on original research leading to a doctoral dissertation, supported by advanced coursework and teaching or research assistantships. Core training typically includes advanced topics in algorithms and theory, machine learning and data science, databases and information retrieval, distributed and operating systems, human–computer interaction, information policy and privacy, and qualitative and quantitative methods for information research.

• Coursework: A tailored combination of graduate seminars and advanced courses to build breadth and depth in chosen subfields (for example: statistical machine learning, deep learning, large-scale data systems, natural language processing, information visualization, HCI methods, and socio-technical studies).
• Research rotation / lab placement: Early-stage students commonly undertake rotations or join a research group to identify a dissertation supervisor and refine research problems.
• Qualifying/Comprehensive exams: Many campuses require a written and/or oral examination to demonstrate preparedness for independent research.
• Dissertation proposal and defence: Students prepare a formal research proposal, conduct original research under faculty supervision and submit and defend a written dissertation.
• Professional development: Training in teaching, grant writing, ethics and responsible conduct of research, and opportunities to present at conferences and publish in peer‑reviewed venues.

Entry requirements

Applicants are expected to hold a relevant master’s degree or an exceptional bachelor’s degree with strong preparation in computer science, information science, statistics, mathematics or a closely related discipline. Typical evidence of suitability includes a record of high academic achievement, strong letters of recommendation (preferably addressing research potential), a clear statement of research interests, and examples of prior research or technical work such as publications, technical reports or project portfolios.

• Academic background: Undergraduate and/or graduate coursework in programming, algorithms, data structures, mathematical foundations (linear algebra, probability, statistics) and discipline‑specific subjects.
• Research experience: Prior research, laboratory experience or substantial project work is highly valued; demonstrated ability to produce technical writing or peer‑reviewed publications strengthens an application.
• Application materials: Statement of purpose outlining research interests and potential faculty collaborators, curriculum vitae, and multiple academic references. Additional requirements such as standardised tests or writing samples vary by campus and programme and should be checked with the specific campus.
• English proficiency: Where English is not a first language, applicants must meet the University of California campus English requirements.
• Funding consideration: Admission decisions often consider fit with available faculty advisers and funding sources; prospective students are encouraged to contact potential supervisors before applying.

Career prospects

Graduates of the PhD in Computer and Information Sciences and Support Services pursue a range of careers that draw on deep technical expertise and strong research skills. Common career pathways include academic faculty and postdoctoral positions, research scientist roles in industrial research labs, senior data scientist or machine learning engineer positions, product research and development in technology companies, UX and information architecture research, policy and ethics roles related to information governance, and leadership positions in startups or public sector organisations.

• Academic research and teaching (tenure-track faculty, postdoc)
• Industrial research and advanced engineering (research scientist, principal engineer)
• Data science, analytics and AI product roles
• Human-centred design and user research
• Information policy, privacy and governance positions in government or NGOs
• Founding or senior technical leadership in technology startups

Why study at University of California

The University of California system offers access to a large and diverse research ecosystem spanning multiple campuses, each with strengths in different areas of computing and information science. Students benefit from world‑class faculty, interdisciplinary collaboration across computer science, information schools, engineering, social sciences and health, and extensive research facilities and computing resources.

• Interdisciplinary opportunities: Strong ties between departments and institutes support work that combines technical, human and policy perspectives.
• Research infrastructure: Access to advanced laboratories, high‑performance computing, large datasets and partnerships with national labs and industry research groups.
• Industry connections: Proximity to major technology hubs and established industry collaborations provide internships, research partnerships and career pathways.
• Funding and mentorship: PhD students are commonly supported through a combination of fellowships, teaching and research assistantships and receive close mentorship from faculty advisors.
• Vibrant academic community: Regular seminars, workshops, and international conferences hosted by the University of California campuses enable students to build networks and disseminate their work.