Computational Precision Health

University of California, Berkeley

About the Program

Computational Precision Health (CPH) is an exploding field across both academia and industry. This rapidly evolving field integrates the tremendous advances in data science and data availability that have occurred over the past decades with expertise in clinical medicine, public health, and health care systems to enable a paradigm shift in the ways we treat and prevent disease. Advances in data and analytics open the door to faster deployment of more effective health interventions, but this potential can only be achieved if the underlying computational and analytic tools are conceived, tested, and validated for the health and health care needs of diverse individuals and communities. The field of Computational Precision Health aims to realize this potential.


A new PhD in Computational Precision Health will welcome its inaugural cohort in fall 2023.

The PhD in Computational Precision Health leverages and bridges the complementary expertise and incredible resources of UC Berkeley and UCSF to create an unparalleled and truly unique learning environment. Students in the PhD in Computational Precision Health will develop skills and expertise in both the computational sciences (machine learning and AI, natural language processing, statistical inference and modeling, data standards, parallel computing and data at scale, etc.) and health sciences (clinical decision sciences and cognitive informatics, clinical delivery, clinical research, implementation science, health information policy, etc.) 


Students will develop the ability to work in interdisciplinary teams from ideation to development, testing, and validation in the real world. Coursework will be complemented by extensive and early interaction with world-class faculty—through research rotations, seminar series, and practicums—at the intersection of computation and health, and will develop proficiency in cross-disciplinary research and communication. A focus on diversity, equity and inclusion, human-centered design accommodating diverse users, and the ethical implications and societal impacts of the work will be embedded throughout the program. 

Fall 2024 PhD Applications are open September 15, 2023
More details on curriculum and CPH courses can be found on our website:

Designated Emphasis

The Designated Emphasis in CPH is administered by the joint UC Berkeley/UCSF Computational Precision Health Augmented Graduate Group. The UCB CPH DE allows PhD students from affiliated UCB programs to incorporate CPH courses and advising into their PhD. CPH DE students will receive a solid grounding in the fundamentals of computational precision health, with training in the application of computation to the practice of medicine and public health. Students will be part of an interdisciplinary, intercampus community of UC Berkeley and UCSF scholars with diverse academic backgrounds, providing unique cross-campus opportunities, including direct exposure to the clinical care and health science environment offered at UCSF.

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PhD Admissions

The PhD program in Computational Precision Health welcomes students from a broad range of computational sciences, health sciences, and interdisciplinary backgrounds.

Admission for the PhD in Computational Precision Health is for the Fall semester only. 2024-2025 Graduate Admissions Application opens on September 15, 2023. The Deadline for Applications is early January. Date TBC. (no rolling admissions). Please select Admit Term Fall 2024.

Applications are submitted via the UC Berkeley Graduate Division application portal. More information about requirements.

Designated Emphasis (DE) Admissions

A designated emphasis (DE) is an interdisciplinary specialization, such as a new method of inquiry or an important field of application, which is relevant to two or more existing doctoral degree programs. A DE is not a standalone program, but is offered to complement a student’s current doctoral studies. UC Berkeley PhD students are welcomed to apply as well as students from UCSF affiliate programs. More information.

Students are encouraged apply at least two semesters before your Qualifying Examination by submitting the following materials to the Computational Precision Health Program, by emailing the documents below to

PhD Requirements

Courses may be taken at UCSF or UC Berkeley:

3 Part Cornerstone Series (3 units x 3 quarters)

CPH 200A, CPH 200B and CPH 200C: Computational Precision Health Cornerstone course series (3 unit each course, 3 per quarter in the first year)
This course series, which uses Problem-Based Learning to build student’s ability to work effectively in interdisciplinary teams, from ideation to development, testing, and validation in the real world.

CPH 215: Lab Rotations (at least 4 units x 2 semesters in the first year)
Students will take two 10-week research group rotations in their first year. One rotation will be on each campus, with one rotation in a predominantly computational science “lab” (with a health emphasis) and one in a health science “lab” (with a computational emphasis).

CPH 270: Computational Precision Health Seminar (2 semester units x 6 terms)
Students will enroll in six terms of the doctoral seminar, including the first two terms after matriculation. Seminar will consist of journal club-style discussion of recent literature in computational precision health, talks by guest faculty, and presentations by second and third year students on work in progress.

CPH 201: Computational Precision Health Practicum (2 semester units x 2 terms)
This series, taken during year two of the program, augments the Cornerstone to provide deep and continuing exposure to clinical and public health context in which CPH advances are to be deployed. Students will have in-depth real world exposure to clinical, research, and operational work in inpatient, outpatient, community health, and/or public health settings.

Foundational courses (at least 12 semester units)
Foundational courses are personalized to compliment students’ backgrounds and training, and support their interests. Courses will be drawn from Electrical Engineering and Computer Science, Statistics, Public Health, Epidemiology and Biostatistics, Medicine, and other departments and schools at UCSF and UC Berkeley.

Advanced Electives (at least 6 semester units)
A minimum of two advanced electives are required, and will be determined in consultation with the student’s Academic Advisor

Race and Racism in Science, and Ethics and the Responsible Conduct of Research (2.3 semester units)
UCSF courses
GRAD 202: Race and Racism in Science (2 quarter units=1.3 semester units), which discusses the historical background of systemic racism in scientific research, and
GRAD 214: Ethics and the Responsible Conduct of Research, L. Silva (1.5 quarter units=1 semester unit), which addresses key issues affecting the responsible conduct of scientific research.

Designated Emphasis Requirements


Students admitted to the CPH DE program must complete two semesters of the CPH Doctoral Seminar, and at least 3 courses from the core course list below, in the following two domain areas:

  1. Health and Public Health Sciences
  2. Computing and Statistical Sciences

In order to ensure that the DE confers sufficient additional breadth beyond a student’s home program, students in a primarily computational PhD program (for example, Bioengineering, Electrical Engineering and Computer Science, Computer Science, Statistics, Biostatistics, Computational Biology, Industrial Engineering and Operations Research) will be required to take at least two courses in the health domain; those in Epidemiology and Health Policy will be required to take at least two courses in the Computational Sciences domain. 

Core Courses

Qualifying courses are listed below. Additional courses falling within the two domains below may also qualify, to be approved by the student’s DE advisor.

1. Health and Public Health Science

Clinical Reasoning and Personalized Medicine: diagnosis and treatment, evidence-based medicine
PB HLTH W250BEpidemiologic Methods II4
PB HLTH W226CEconomics of Population Health3
PB HLTH 255DMethods in Social Epidemiology2
PB HLTH 222ABiomedical Innovation Policy3
PB HLTH 235Impact Evaluation for Health Professionals3

2. Computing and Statistical Sciences

COMPSCI 289AIntroduction to Machine Learning4
COMPSCI 286AIntroduction to Database Systems4
COMPSCI C281A/STAT C241AStatistical Learning Theory3
STAT 156Causal Inference4
STAT 154Modern Statistical Prediction and Machine Learning4

In some cases, for example, STAT 154 and STAT 156/STAT 256, an upper division undergraduate course may be acceptable for the DE. This is due to the desire to accommodate students from non-computational PhD programs who may not have the programming, mathematics or statistics prerequisites for corresponding graduate-level coursework.

CPH Doctoral Seminar

In addition, students will participate in at least 2 semesters of the CPH Doctoral Seminar. The seminar will consist of a combination of journal club-style discussion of recent literature in Computational Precision Health, and guest faculty speakers drawn from across the CPH Graduate Group and beyond. This seminar will be held in conjunction with UCSF DE CPH students.

Elective Courses

No Elective courses are required for the Designed Emphasis, but the DE Advisor may guide students on additional courses to supplement their training in this field.

UC Berkeley Affiliated Programs

PhD in Bioengineering

PhD in Electrical Engineering and Computer Sciences

PhD in Computer Science

PhD in Biostatistics

PhD in Statistics

PhD in Computational Biology

PhD in Epidemiology

PhD in Health Policy

PhD in Industrial Engineering and Operations Research

PhD in Information Science

*Students from any PhD program at UC Berkeley are welcome to apply.

Normative Time

No additional time can be added to the normative time of your home department.

Contact Information

Computational Precision Health

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Director, UC Berkeley UCSF Joint Program in Computational Precision Health

Maya Petersen, MD, PhD

Director, UC Berkeley UCSF Joint Program in Computational Precision Health

Ida Sim, MD, PhD

Senior Administrative Officer

Rhiannon Lewis

Graduate Student Affairs Officer

Bianca Victorica

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