Computational Precision Health (PhD)
Degree Offered: PhD
Program Leadership:
Ida Sim, MD, PhD, Program Director, UCSF
Maya Petersen, MD, PhD, Program Director, UCB
Admissions Inquiries:
Bianca Victorica, Graduate Student Affairs Officer
Program Description
The UCSF UC Berkeley Joint Program in Computational Precision Health (CPH) 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.
Faculty
CPH faculty are members of the Joint Augmented Graduate Group in Computational Precision Health. There are currently 42 faculty members: three faculty with primary appointment in CPH, and 39 faculty from multiple departments across UCSF and UC Berkeley. UCSF faculty hail from all UCSF clinical sites, reflecting the diversity of populations and care settings across San Francisco.
Learning Outcomes
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.)
Additional Information
Program Core Faculty
- Find a program faculty list on the program website.
Degree Requirements
- Minimum GPA of 3.0
- All core courses and required activities taken and passed
- Six quarters in residence including a minimum of three quarters (enrolled in 8 units of Research in each quarter) after advancement to candidacy.
- Pass qualifying examination
- Completion and submission of the Dissertation
- For additional details, please see: https://graduate.ucsf.edu/phd-degree
Core Courses
| Code | Title | Units |
|---|---|---|
| COMP HLTH 200A | Computational Precision Health Cornerstone | 3 |
| COMP HLTH 200B | Computational Precision Health Cornerstone | 3 |
| COMP HLTH 200C | Computational Precision Health Cornerstone | 3 |
| COMP HLTH 215 | Lab Rotation | 2-8 |
| COMP HLTH 270 | Computational Precision Health Seminar | 3 |
| GRAD 202 | Racism in Science | 3 |
| GRAD 214 | Responsible Conduct of Research for Basic Scientists | 1.5 |
| CPH Practicum Series (TBD) | 3 units, 2 terms (Second Year) | 3 |
| Foundational Courses (TBD) | Minimum of four classes, selected in close consultation with their Academic Adviser (First Year) or Research Adviser(s) (Second Year) | |
| Advanced Electives (TBD) | Minimum of two advanced electives, based on intended dissertation work. |