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Assistant/Associate Professor of Computational Precision Health (UCSF UC Berkeley Joint Program in CPH)

University of California - San Francisco
United States, California, Berkeley
Nov 07, 2024

Application Window


Open date: August 12, 2024




Most recent review date: Wednesday, Sep 11, 2024 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: Thursday, Feb 12, 2026 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.



Position description

The UCSF UC Berkeley Joint Program in Computational Precision Health is seeking an Assistant/Associate Professor of Computational Precision for a full time faculty position. The selected candidate will be appointed at the level of Assistant/Associate Professor in the In Residence series depending on qualifications.

The faculty member will establish a research program focused on leveraging machine learning methods to integrate multiple modalities of data (e.g., EHR, imaging, genomics) including environmental exposure data into computational models for prevention, diagnosis, and treatment of breast cancer, and for mechanistic understanding of breast cancer etiology.

Successful applicants are expected to develop a nationally recognized program and collaborate across disciplines to develop research initiatives in computational precision health. They will be expected to conduct teaching and research at both campuses in the true spirit of the joint program. The candidate will be responsible for teaching CPH PhD students and potentially undergraduates at UC Berkeley as well. The appointee will be given laboratory space at UCSF and/or UC Berkeley.

In addition, this faculty member will join a dynamic breast cancer research team at UCSF's Breast Oncology Program, a National Cancer Institute-designated cancer center. Candidates should have experience with relevant AI/ML methods, epidemiologic modeling of toxic exposures, and cost-benefit analyses of risk-based screening and risk reduction policies. Successful candidates will therefore have knowledge of cancer registries, databases that track residential history, registries of hazardous exposures, and machine learning methods for risk prediction, as well as knowledge of personalized risk-based screening algorithms and cost analyses.

Candidates should demonstrate evidence of strong research productivity, potential for securing extramural funding, and a commitment to excellence in teaching and mentoring and to collaborative research. We welcome scholars with a commitment to and track record of promoting diversity, equity and inclusion in the realms of research, teaching, and/or service. Experience with training, mentoring, and/or research in low-resource countries will be highly favorable. The ability to work well in a multidisciplinary team environment is essential.

Qualifications: Completion of a doctoral degree (e.g., PhD, MD, DNP, PharmD, DDS, or equivalent) or equivalent international degree. Candidates who have an MD or equivalent and who intend to be clinically active must also be Board-certified or Board-eligible in their specialty and must possess (or be in the process of obtaining) a valid California medical license and valid DEA.

Preferred/Desirable Qualifications: Candidates are preferred to hold a doctorate degree in computer science, health informatics, statistics, biostatistics, data science, epidemiology, engineering, operations research, economics, health services research, information sciences, or other computational fields, and/or a medical, dental, nursing, pharmacy or public health degree with demonstrated experience/training in the computational sciences or health informatics.

The posted UC salary scales set the minimum pay determined by rank and step appointment. See [Table 5] https://www.ucop.edu/academic-personnel-programs/_files/2023-24/oct-2023-acad-salary-scales/t5-summary.pdf. The minimum base salary for this position is $121,100-$189,500. This position includes membership in the health sciences compensation plan https://ucop.edu/academic-personnel-programs/_files/apm/apm-670.pdf which provides for eligibility for additional compensation.

Please apply online at with a CV, cover letter, statement of research, statement of teaching, statement of contributions to diversity, three relevant publications, and contact information for three references at https://aprecruit.ucsf.edu/JPF05093. To receive full consideration, please submit all materials prior to the initial review date. However, this position will remain open until filled. Applicants' materials must list current and/or pending qualifications upon submission. The selected candidate must meet all of the qualifications at the time of appointment.


Application Requirements
Document requirements
  • Cover Letter


  • Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).


  • Statement of Research


  • Statement of Teaching


  • Statement of Contributions to Diversity - Please see the following page for more details: Contributions to Diversity Statement


  • Relevant Publication #1


  • Relevant Publication #2


  • Relevant Publication #3


Reference requirements
  • 3 required (contact information only)

About UC San Francisco

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

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.


Job location
San Francisco and/or Berkeley, CA
Applied = 0

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