How to Apply
For consideration of this position, applicants must submit the following materials as one document: 1) a cover letter describing their interest in working in computational approaches to understanding the epidemiology of Alzheimer's disease and related dementias, and 2) a current CV.
Job Summary
The Department of Epidemiology is seeking a postdoctoral research fellow-with a record of accomplishment in computational epidemiology and modeling applied to aging epidemiology or adjacent field-to contribute to studies seeking to answer epidemiological questions about cognitive transitions across the older adult life course and interventions targeting modifiable dementia risk factors. Primary responsibilities include the design and conduct of data analysis of longitudinal cohorts and simulation models to project trends and examine potential interventions, as well as the preparation of scientific manuscripts as lead and co-author. There may be opportunities available for collaboration on a range of funded studies in the area of aging research, as well as for participation in the preparation and submission of extramural research grants.
This position, funded by a National Institutes of Aging grant, will be under the supervision of Dr. Andrew Brouwer, a computational epidemiologist whose research leverages mathematical and statistical modeling for inference in epidemiology. The University of Michigan has a vibrant and dynamic intellectual community for aging research, including the Center for Lifecourse Epidemiology & Aging Research, the Michigan Alzheimer's Disease Research Center, the Center to Accelerate Population Research in Alzheimer's, the Claude D. Pepper Older Americans Independence Center, and the Institute of Gerontology, among others.
Responsibilities*
- Data management: Manages the organization, documentation, merging, cleaning, and storage of complex population datasets. Creates final analytic datasets
- Data analysis and modeling: Designs and executes complex data analyses and simulation models. Independently interprets results, including creation of data tables, visualizations, and reports for presentation
- Manuscript preparation: Conceptualizes and contributes to the writing of scientific manuscripts as lead author and co-author
- Collaboration and mentorship: Provide collaborator feedback and supplementary mentorship to master's- and PhD-level students engaged in related research projects
- Grant preparation: Assists in acquiring extramural research funding, including the technical portions of grant proposals
Required Qualifications*
- Doctorate in epidemiology or other public health science. Applicants with PhD in computational or quantitative fields (statistics, applied mathematics, etc.) are encouraged to apply if they meet the other criteria. Applicants must have a conferred doctorate degree prior to the start of the fellowship
- A record of accomplishment in computational epidemiology and modeling applied to aging epidemiology or adjacent field, as evidenced by publications, presentations, and training
- Prior training or research in simulation modeling
- Proficiency in programming in R (preferred) or Python. Excellent skills in data management and analysis, data visualization, and scientific communication
Desired Qualifications*
The following qualifications are not required or expected but should be highlighted in the application materials if relevant.
- Prior experience in the analysis of longitudinal cohorts
- Prior experience with multistate transition models and microsimulation models, or similar approaches
- Prior experience with the National Alzheimer's Coordinating Center Uniform Data Set, the Health and Retirement Study, or the Study of Women's Health Across the Nation
- Prior experience in women's health, cardiovascular disease, or biomarkers of ADRD (or biomarkers of aging more broadly)
Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.
Work Locations
This position allows for a hybrid work schedule. The selected candidate will be expected to work on-site 2 days per week.
Additional Information
This is a term-limited position for one-year from the start of the appointment, with possibility of extension contingent upon funding and performance.
We are seeking an experienced and dynamic staff leader/member with a commitment to contributing to a welcoming environment for all members of our community.
Anticipated start date: Between November 1, 2026 and January 1, 2027.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled any time after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.