Open date: July 25, 2022
Most recent review date: Friday, Sep 23, 2022 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, Jan 25, 2024 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.
Faculty Position in Data Science and Computational Pathology
UCSF Department of Pathology
The Department of Pathology of the University of California at San Francisco seeks outstanding candidates for a new faculty position at the level of Assistant, Associate or Professor in the In-Residence or Ladder Rank series. The successful candidate will lead the effort in a research initiative that aims to accelerate the pace and sophistication of data acquisition, analyses, and integration in computational pathology. The specific areas of expertise include, but not limited to, single cell biology, spatial transcriptomics and proteomics, segmentation multiplexing image analysis, tissue microarrays, machine learning, artificial intelligence, etc. The candidate will be expected to direct an independent basic or translational research program that leverages a large clinical dataset to investigate the mechanisms of human disease, including cancer biology, immunobiology, organ transplantation biology, or neurobiology. Additional duties will include departmental and university teaching for graduate students, medical students, house-staff and fellows. Candidates will have a track record of innovative accomplishment in basic/translational research and a keen interest in working within a highly collaborative, multidisciplinary environment. The candidate will have or seek to develop a robust research portfolio of extramural grant support. Candidates will be proposed for membership in the Biomedical Science (BMS) Graduate Program. The candidate will be based at the Parnassus Heights campus. Candidates will collaborate extensively with UCSF clinical and basic scientists and with leaders of other clinical data units, including the ImmunoX Initiative, the UCSF Helen Diller Family Comprehensive Cancer Center, and the Bakar Computational Health Sciences Institute.
The successful candidate must possess an MD and/or PhD degree, or equivalent degree. Candidate with MD and clinical training in Anatomic or Clinical Pathology must be Board Certified or Board Eligible at the time of appointment and be eligible for a medical license in California at the time of appointment. Individuals with a documented record of grant support are highly desirable. Applicant’s materials must list (pending) qualifications upon submission. Salary and appointment rank will be commensurate with the candidate’s experience and training.
Applicants must submit a curriculum vitae, cover letter, statement of research, statement of teaching, statement of contributions to diversity, and names and contact info of three references within 60 days of the appearance of this announcement to: https://aprecruit.ucsf.edu/JPF04057.
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: https://diversity.ucsf.edu/contributions-to-diversity-statement
- 3 required (contact information only)
As a condition of employment, you will be required to comply with the University of California SARS-CoV-2 (COVID-19) Vaccination Program Policy found here: https://policy.ucop.edu/doc/5000695/SARS-CoV-2_Covid-19.
UC San Francisco seeks candidates whose experience, teaching, research, or community service that 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.