Work type: Non-Tenure Line (Research), University Medical Line, University Tenure Line
Location: Stanford University
Categories: School of Medicine
The Quantitative Sciences Unit within the Department of Medicine's Biostatistics Section at Stanford University School of Medicine seeks a faculty member to join at the rank of Assistant, Associate, or Full Professor in the Non-Tenure Line Research, University Tenure Line or University Medical Line.
Applicants should have a PhD, MD/PhD, MD/MPH or MD with strong quantitative and methodologic research training in Biostatistics, Statistics, Epidemiology or related field under the larger umbrella of the Quantitative Sciences with a focus on clinical and translational science that aligns with the department's strategic initiatives. Areas of specialization may include but not limited to - clinical trials, artificial intelligence and machine learning, predictive modeling, causal inference, study design, and bio- and clinical informatics - with a strong interest in solving problems that affect social, global, public, and population health. Applicants should be interested in collaborating with clinical and translational investigators in team settings on complex problems that may require novel study design; creativity in analyzing data using large databases; developing predictive models in high dimensions.
The predominant criterion for appointment in the University Tenure Line is a major commitment to research and teaching. The major criteria for appointment for faculty in the University Medical Line shall be excellence in the overall mix of clinical care, clinical teaching, scholarly activity that advances clinical medicine, and institutional service appropriate to the programmatic need the individual is expected to fulfill. The major criterion for appointment in the Non-Tenure Line Research is evidence of high-level performance as a researcher for whose special knowledge a programmatic need exists. Faculty rank and line will be determined by the qualifications and experience of the successful candidate.
The Section of Biostatistics lives within the Division of Biomedical Informatics Research in the Department of Medicine. Its mission is to develop data science infrastructure that fills critical gaps at Stanford School of Medicine and that ensures that the field of medicine advances through the practice of rigorous data science. To that end, the Biostatistics Section has established a home for the scholarship of collaborative biostatistics to advance human health through the conduct of rigorous and informative studies. We expect the successful candidate to engage primarily in collaborative research while developing an independent research agenda in the methods directly stemming from collaborative work. The candidate will lead methodological initiatives that contribute to building critical research infrastructure at Stanford and beyond, will serve as the leading quantitative scientist on collaborative initiatives, and will mentor the current and next generation of clinical and translational investigators including both clinical investigators and practicing data scientists. The candidate is expected to identify and resolve methodological issues that arise in collaborative research, as a major expectation is to develop a research program in methodological areas that will directly benefit the candidate's collaborative research.
Criteria for the position include evidence of the potential to obtain peer reviewed research funding and excellence in collaborative biostatistics, teaching, and mentorship appropriate to fulfill the programmatic needs of the Biostatistics Section and the Quantitative Sciences Unit.
The university's central functions of research and education depend on freedom of thought, and expression. The Department of Medicine, School of Medicine, and Stanford University value faculty who will help foster an open and respectful academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and perspectives. Candidates may choose to include as part of their research and teaching statements a brief discussion about how their work and experience will further these values.
Interested candidates should submit their curriculum vitae, a brief letter outlining their interests and the names of three references (who will not be contacted without prior consent) to: Quantitative Sciences Unit: Open Rank Faculty Search
Contact Junie Urbano, Faculty Affairs Specialist for Recruitment at for more information. Applications will be reviewed beginning June 2025 and accepted until the position is filled.
The expected base pay range for this position is:
Assistant Professor: $223,000 - $251,000
Associate Professor: $268,000 - $295,000
Professor: $318,000 - $358,000
This pay range reflects base pay, which is based on faculty rank and years in rank. It does not include all components of the School of Medicine's faculty compensation program or pay from participation in departmental incentive compensation programs. For more information about compensation and our wide-range of benefits, including housing assistance, please contact the hiring department.
Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years in rank, training, and field or discipline; internal equity; and external market pay for comparable jobs.
Stanford is an equal employment opportunity and 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, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University's research, teaching and clinical missions.
Advertised: 30 Apr 2025 9:00 AM Pacific Daylight Time
Applications close:
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