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Assistant, Associate, Full Professor (clinical/translational)- UCSF Bakar Computational Health Sciences Institute (BCHSI)

Recruitment Period

Open date: October 10th, 2018

Last review date: Tuesday, Jan 15, 2019 at 11:59pm (Pacific Time)
Applications received after this date will be reviewed by the search committee if the position has not yet been filled.

Final date: Friday, Apr 10, 2020 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.


Job Description (clinical/translational)
Assistant, Associate, Full Professor
UCSF Bakar Computational Health Sciences Institute

The Bakar Computational Health Sciences Institute (BCHSI) at UCSF is looking to recruit faculty at the Assistant, Associate, or Full Professor level. BCHSI prefers candidates who have a strong background in clinical informatics, machine learning, and/or network/mathematical modeling with an interest in health research; and to have demonstrated significant achievement or promise in their field. Candidates are required to hold a doctorate degree in informatics, computer science, epidemiology, biostatistics, or a related discipline with demonstrated experience/expertise in informatics, data science, and/or a medical, dental, nursing or pharmacy degree with demonstrated experience/training in informatics or data science. A primary affiliation with BCHSI will be provided, along with an academic appointment within the UCSF Department of Epidemiology & Biostatistics or another department closely allied with the applicant’s scholarly or clinical expertise. Candidates will be expected to teach and/or mentor graduate and medical students while developing extramurally-sponsored research programs.

About Bakar Computational Health Sciences Institute:
The Bakar Computational Health Sciences Institute ( is a critical component of a global UCSF initiative in Precision Medicine, which seeks to aggregate and integrate vast, disparate datasets to advance understanding of biological processes, determine mechanisms of disease, and inform diagnosis, prevention, and treatment. Since its formation in 2015, the Institute has established a cohort of 50 affiliated faculty who represent a diverse array of departments drawing from UCSF’s four top-ranked professional schools (Dentistry, Medicine, Nursing and Pharmacy) and Graduate Division; and whose talents are evidenced by a host of honors including 5 National Academy of Medicine members, 3 National Academy of Sciences members, 2 members of the American Society for Clinical Investigation, 3 NIH Director’s Awards, 2 Sloan Foundation Fellows, an HHMI Faculty Scholar, and MacArthur Foundation Fellow. Bakar Institute investigators employ computational strategies in basic, translational, clinical and population-based biomedical research within the interest areas of biological modeling, precision oncology, clinical informatics, computational neuroscience, computational pharmacology, deep machine learning and data visualization, population precision medicine, and very large data molecular measurements.

We foster collaborations within the UCSF Medical Center, named among the nation’s premier medical institutions for 15 consecutive years, as well as the statewide UC system, including 6 academic medical centers (Davis, Irvine, Los Angeles, Riverside, San Diego, San Francisco) comprising UC Health. As Chief Data Scientist for UC Health, our Bakar Institute Director works to ensure the integration of all UC Health data into an accessible Clinical Data Warehouse representing more than 15 million patients, and supports our investigators in their efforts to transform this unparalleled wealth of information into advancements in knowledge to improve health.

UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.

Please apply online and submit CV, cover letter, statement of contributions to diversity, statement of research, statement of teaching, and 3 references who we may contact directly to:

Job location

San Francisco, CA


Document requirements
Reference requirements
  • 3 required (contact information only)