Computational Precision Health (PhD)

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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