Assistant Professor Of Biostatistics (Health Data Science) - PH 343

The Brown University School of Public Health and the Data Science Institute are pleased to announce an opening for a tenure-trackAssistant Professor with emphasis in Health Data Science. This interdisciplinary position will have a primary appointment in Biostatistics and a secondary appointment in the Brown Data Science Institute, and will join a growing and vibrant faculty. In this global search, we are seeking candidates working at the interface between public health and data science with demonstrated ability for innovative, high impact research in health data science, broadly defined, classroom teaching, and student advising and mentoring.

We seek exceptional candidates who will develop an independent, innovative research program in statistical methodology, particularly related to deep learning, data fusion, analysis of high-dimensional and real-world data, and the design and evaluation of AI tools for health. Although we welcome candidates with broad interests in health-related research, priority domain areas include mental health, aging, and Alzheimers Disease. The School of Public Health, the Data Science Institute, and the broader University provide outstanding opportunities for collaboration with world-class researchers in computational mathematics, brain sciences, computational biology, alcohol and addiction research, gerontology, and health care and policy. The Department of Biostatistics has a rich research portfolio in causal inference, analysis of high-dimensional and -omics data, Bayesian methods, and clinical trials, with active collaborations in cancer, aging, HIV, and the analysis of large-scale health data.

The School of Public Health and the Data Science Institute are responsible for teaching a growing number of students at the undergraduate, Masters, and PhD levels. More information about our educational and training programs can be found at https://www.brown.edu/academics/public-health/academics and https://dsi.brown.edu/academics.

Candidates must have a doctoral degree in a methodologic field such as (bio)statistics, epidemiology, computer science, operations research, industrial engineering, applied mathematics, or economics. The candidate must have demonstrated excellence in innovative and high-impact research in data science (broadly defined) and in classroom teaching and student advising, and have interest and demonstrated ability for engaging in interdisciplinary public health research. All candidates must show evidence of excellent oral and written communication skills.

Please apply online at Interfolio. Review of new applications will begin on November 15, 2025. Full consideration will be given to all applications received by that date. Applications received after the priority deadline will be reviewed until the position is filled or the search is closed.

Interested applicants should submit a letter of application and curriculum vitae through Interfolio. The letter of application should include a teaching statement, a research statement, and a description of the applicant?s contributions to data science. Candidates should address how they would contribute to the research and/or teaching missions of our diverse and inclusive university community. The candidate should arrange for three letters of reference to be uploaded to Interfolio.

Potential applicants are invited to contact Jerry Logan ([email protected]); for additional details contact the Search Committee Chair Rebecca Hubbard ([email protected]).

Brown University provides equal opportunity and prohibits discrimination, harassment and retaliation based upon a person?s race, color, religion, sex, age, national or ethnic origin, disability, veteran status, sexual orientation, gender identity, gender expression, or any other characteristic protected under applicable law, in the administration of its policies, programs, and activities. The University recognizes and rewards individuals on the basis of qualifications and performance. The University maintains certain affirmative action programs in compliance with applicable law.