Post-doctoral Associate

Statistics Interest Group

Minneapolis (MN)

On-site

USD 65,000 - 75,000

Full time

14 days+

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Job summary

The University of Minnesota, Division of Biostatistics & Health Data Science seeks a Post-Doctoral Associate to work with leaders in causal inference and clinical trial design. The appointment is 1-2 years, renewable, with flexible work arrangements and possible extension.

Responsibilities include theory development, simulations, data analysis, interpretation, presentation, and manuscript preparation; location Minneapolis, on-site with potential remote work options.

Qualifications

  • PhD in biostatistics, statistics, or a related discipline.
  • Preferred qualifications include prior research in causal inference or innovative trial design and analysis.

Responsibilities

  • Theoretical development and methodological work in causal inference.
  • Simulation studies to evaluate new methods.
  • Data analysis and interpretation of results.
  • Presentation of results at seminars and conferences.
  • Manuscript preparation for publications.

Skills

Causal inference research
Clinical trial design

Education

PhD in biostatistics or statistics

Job description

This is a current listing of job announcements related to Statistics.To submit a job for posting please use the Statistics Job Submission Form . Please note that jobs are posted within 24hrs of submission. If you have any questions, comments, or need to make acorrectionregarding your job announcement, please contact jobs@stat.ufl.edu .

University of Minnesota, Division of Biostatistics & Health Data Science - Post-doctoral Associate
Company Name University of Minnesota, Division of Biostatistics & Health Data Science
Position Title Post-doctoral Associate
Company Information

The Division of Biostatistics & Health Data Science (https://www.sph.umn.edu/academics/divisions/biostatistics/) 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 (CCBR; https://ccbr.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 (https://ctsi.umn.edu/services/statistical-support/biostatistical-support), the Analytics Core of the Masonic Institute for the Developing Brain (https://midb.umn.edu/research/analytics), the Innovative Methods and Data Science (https://med.umn.edu/clhss/activities/imds) and RapidEval Programs (https://med.umn.edu/clhss/activities/rapideval) in the Center for Learning Health Systems Sciences, and the Genomics Data Commons (https://www.sph.umn.edu/research/centers/genomic-data-commons/).

Duties and Responsibilities

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 (https://directory.sph.umn.edu/bio/sph-a-z/joseph-koopmeiners), Dr. David Vock (https://directory.sph.umn.edu/bio/sph-a-z/david-vock), and their collaborators, and will be a member of the Minnesota Complex Innovative Design Research Lab (M-CIDeR; https://sites.google.com/umn.edu/m-cider/home). 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.

Position Qualifications
Required Qualifications
  • PhD in biostatistics, statistics, or a related discipline
Preferred Qualifications
  • Prior research in causal inference or innovative trial design and analysis
Salary Range $65,000 - $75,000 annually, depending on education/qualifications/experience

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, https://hr.umn.edu/jobs/Why-UMN/Benefits-UMN, for more information regarding benefit eligibility.

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