Postdoctoral Associate

About The Opportunity

The Department of Epidemiology at the Boston University School of Public Health invites applications for a Postdoctoral Associate Research Fellow to conduct NIH-funded epidemiologic research on the effects of environmental chemical exposures on reproductive health. This role will involve working with data from the Study of Environment, Lifestyle, and Fibroids (SELF), a prospective cohort study of Black women. The focus will be on evaluating associations between environmental chemical exposures (including mixtures) and reproductive outcomes, with a particular emphasis on fertility. This position offers the chance to develop expertise at the intersection of reproductive epidemiology, environmental epidemiology, and advanced statistical methods. The Postdoc is expected to work independently, take intellectual leadership in statistical analysis, manuscript preparation, and dissemination of findings, while collaborating with investigators across related disciplines. A key aspect of the fellowship will be applying mixtures modeling approaches to characterize the reproductive effects of correlated and co-occurring environmental chemical exposures.

Key Responsibilities

• Design and conduct epidemiologic analyses using data from the Study of Environment, Lifestyle, and Fibroids (SELF) cohort.
• Evaluate associations between environmental chemical exposures and reproductive outcomes.
• Apply and extend advanced statistical methods for evaluating the health effects of chemical mixtures and correlated environmental exposures.
• Develop analytic approaches that address exposure correlation, nonlinearity, interactions, and potential confounding in environmental epidemiologic studies.
• Lead the preparation and submission of manuscripts for peer-reviewed journals.
• Present research findings at national and international scientific conferences.
• Contribute to the development of grant applications focused on environmental and reproductive health.
• Collaborate with multidisciplinary investigators in epidemiology, environmental health, biostatistics, and reproductive health.
• Contribute to data management, quality control, analytic planning, and interpretation of findings.
• Mentor and support students in epidemiologic methods, statistical programming, and scientific writing.

Requirements & Tech Stack

• Doctoral degree (PhD, ScD, or equivalent) in Epidemiology, Environmental Health, or a closely related discipline.
• Strong training in epidemiologic methods and quantitative research.
• Demonstrated experience with environmental mixtures modeling, including methods for evaluating health effects of multiple correlated chemical exposures.
• Experience conducting analyses using large observational or longitudinal epidemiologic datasets.
• Strong programming and statistical skills in SAS, R, or a comparable statistical programming language.
• Demonstrated ability to independently design, conduct, and interpret epidemiologic analyses.
• Excellent scientific writing and oral communication skills.
• Strong interest in reproductive and environmental health research.

Preferred Qualifications

• Experience in environmental epidemiology, reproductive epidemiology, infertility research.
• Experience with environmental chemical exposures, such as PFAS, heavy metals, persistent pesticides, or other endocrine-disrupting chemicals.
• Familiarity with advanced methods for mixtures analysis, such as quantile g-computation, Bayesian kernel machine regression, weighted quantile sum regression, or related approaches.
• Experience with time-to-event analyses of health outcomes.
• Knowledge of causal inference methods, including directed acyclic graphs, multiple imputation, marginal structural models, and mediation analysis.
• Experience analyzing longitudinal data.
• Grant writing experience.
• Record of peer-reviewed publications commensurate with career stage.

Salary Information

• Minimum Salary: $67,500.00
• Maximum Salary: $85,000.00
• The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, training and internal pay comparison. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.