Post-doctoral Associate

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The Division of Biostatistics & Health Data Science (https://(Use the "Apply for this Job" box below).) currently includes 35 faculty members and 61 staff. Faculty regularly publish in the top methodological journals across all major biostatistical research areas, including causal inference, clinical trials, statistical genetics, bioinformatics, genomics and proteomics, analysis of spatial and longitudinal data, biomedical imaging, survival analysis, meta-analysis and data synthesis, and mobile health. Division faculty are active in a wide range of collaborative research projects including high-profile studies of cancer, cardiovascular disease, infectious disease, dentistry and periodontology, psychiatry/psychology, transplantation, chronic and neurodegenerative diseases, and tobacco control.

The Division’s Coordinating Center for Biometric Research (CC ; https://cc .biostat.umn.edu/) is considered a field leader in clinical trial coordination and has been instrumental in designing and executing seminal vaccine and treatment trials in HIV/AIDS, Ebola, influenza, and COVID-19. Several Division faculty have leadership roles in major cross-disciplinary initiatives, including the Biostatistical Design and Analysis Center (BDAC) of the Clinical and Translational Science Institute and the Biostatistics Core of the Masonic Cancer Center (),

the Analytics Core of the Masonic Institute for the Developing Brain (), the Innovative Methods and Data Science () and Rapid Eval Programs () in the Center for Learning Health Systems Sciences, and the Genomics Data Commons (https://).

The Division of Biostatistics & Health Data Science in the School of Public Health at the University of Minnesota is seeking applications for a full-time Post-Doctoral Associate position. The Post-Doc will work with Dr. Joe Koopmeiners (), Dr. David Vock (), and their collaborators, and will be a member of the Minnesota Complex Innovative Design Research Lab (M-CIDeR; ). Research will focus on developing, implementing, and applying novel statistical methods for causal inference motivated by tobacco regulatory science, with a specific focus of understanding the public health impact of a nationwide nicotine standard for cigarettes.

Specific topics include detecting and evaluating treatment effect heterogeneity, causally interpretable meta-analysis, data integration, and sensitivity analysis. The successful candidate will also have the opportunity to collaborate on the implementation of and methodological development of complex, innovative clinical trial designs through M-CIDeR. Specific responsibilities will include theoretical development, simulation studies, data analysis, interpretation of results, presentation of results, and manuscript preparation.

This annually renewable appointment is for 1-2 years, possibly extendable to year 3, conditional on satisfactory performance and funding availability.

The position is open immediately and will remain open until filled.

• PhD in biostatistics, statistics, or a related discipline

• Prior research in causal inference or innovative trial design and analysis

The University of Minnesota endorses a "Work. With Flexibility." and we offer a flexible work environment that meets the needs of our students, faculty, staff, and partners we serve. The successful candidate will be provided University-configured equipment and supportive technology tools, however, they are expected to have access to a reliable internet connection for duties undertaken remotely. Work arrangements will be discussed during the interview.

Onsite location:
University Office Plaza, 2221 University Ave SE, Minneapolis, Twin Cities Campus
- East-bank.

Please visit the Office of Human Resources website,  for more information regarding benefit eligibility.