Mid-Career Faculty, Biostatistics
Listed on 2026-07-29
-
Research/Development
Data Scientist, Academic
Mid-Career Faculty, Biostatistics
Details
The Division of Biostatistics in the Department of Population Health Sciences (PHS) at the Spencer Fox Eccles School of Medicine at the University of Utah has openings for mid-career faculty members, who have a history of funded research as a PI/MPI and who work on the analysis of modern data sources and study designs, and expand the Division's methodological and collaborative strengths.
We are looking for candidates who will lead methodological research, collaborate with biomedical researchers, support and develop grant proposals, teach in the PhD Biostatistics program, and mentor and advise graduate students. We are particularly interested in candidates who possess the research skills and experience required to successfully become leaders in multidisciplinary research teams within the institution and in national and international research networks, as well as pursue independent and collaborative methodological research in Biostatistics.
We are especially excited about candidates who are interested in mentoring junior faculty and in future leadership roles.
Faculty members in the Division of Biostatistics collaborate closely and hold affiliations with the Huntsman Cancer Institute (HCI), Study Design and Biostatistics Center (SDBC) and Utah Data Coordinating Center (DCC). The University of Utah School of Medicine is investing heavily in data science through the DELPHI Initiative and Responsible AI (RAI) Initiative. There is also substantial investment in genomics including the Center for Genomic Medicine (CGM).
See below for more information on HCI, DCC, SDBC, DELPHI, RAI and CGM.
Methodological interest and experience are desired, but not limited to, the following areas: (1) 'omics (e.g., metabolomics, transcriptomics, metagenomics), (2) data fusion, (3) machine learning, (4) intensive longitudinal data analysis, (5) functional data analysis, (6) statistical computing, (7) generative AI and (8) novel study design.
The University of Utah offers highly competitive salaries and start-up packages and exceptional benefits. Applications will be reviewed on a rolling basis, and the start date is flexible. The job announcement will remain active until the positions are filled.
Minimum Qualifications
A PhD in biostatistics or related discipline is required, as well as a demonstrated excellence in collaborative and methodological research. The candidate should be mid-career and have (1) a history of funding as PI/MPI, (2) an interest in mentoring graduate students and junior faculty, and (3) a commitment to team science. Candidates should apply online at
Required materials:
- Letter of interest (cover letter)
- CV
- Research statement
- Teaching statement
- Exemplar publications that highlight expertise in biostatistics
- List of 3 references
Questions about these positions should be directed to the search committee chair:
Daniel Scharfstein.
About the Division of Biostatistics
We are a tight knit entrepreneurial group of six faculty. We address important biomedical problems through deep collaborations with researchers at the University of Utah and beyond. We have deep connections with the Division of Epidemiology (within the Department of Internal Medicine), the Utah Data Coordinating Center, the Huntsman Cancer Institute, the Veterans Administration, and Intermountain Health. We conduct methodological research that is motivated by the problems we encounter during our collaborations.
We have an internationally diverse PhD students who receive training both in the classroom and through mentored collaboration. We are surrounded by large databases that can be used to address important scientific questions. For example, The Utah Population Database (UPDB) is the world's largest resource for tracking diseases in families, with more than 11 million people in large, multigenerational pedigrees, linked to tens of millions of medically relevant records.
The Enterprise Data Warehouse (EDW) contains data extracted from many of the institution's disparate source systems, including patient, visit, clinical, operational, financial, and research data. It contains data on more than 2.5 million…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).