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Our research is targeted towards investigating environmental influences on reproductive health, with a focus on reducing the burden of menstrual dysfunction, subfertility, and pregnancy loss. Our work is hypothesis-driven; translating biological research from the bench to human populations, and seeking interventions for improving public health. To that end, we leverage multiple prospective studies, and we contribute to the development of high-quality and innovative research methods including a focus on digital health applications or “apps”.
Postdoctoral fellows work with data from numerous sources including the Investigation of Vitamin D and Menstrual Cycles Trial (the inVitD Trial), the Early Pregnancy Study (EPS), Time to Conceive, the Study of Environment Lifestyle and Fibroids (SELF), the Sister Study, and the Apple Women’s Health Study. Opportunities also exist for large consortium-based projects. The FRHG also collaborates with outside investigators to access high-quality data sources that can support our research mission.
Postdoctoral fellows in the FRHG develop a research portfolio that fits their interests and training goals, and are encouraged to build on existing resources to develop new projects that become the basis for transition to independence research awards (such as K99/R00 awards). Fellows are encouraged to take advantage of the rich and varied training and career development opportunities offered at NIEHS. The training environment is enriched by proximity and access to local universities (e.g., University of North Carolina, NC Central University, NC State University, and Duke University), where Epidemiology Branch investigators have adjunct appointments. Opportunities for mentoring undergraduate and graduate students are available. NIEHS offers comprehensive training and career development opportunities for fellows.

Candidates who earned a doctoral degree within the past five years in epidemiology or a closely related field, or those who earned a medical degree and have advanced graduate training in epidemiology or a related field, are invited to apply. Applicants must have extensive experience with epidemiologic or statistical data analysis. Preference will be given to candidates with demonstrated research interests in FRHG focus areas (e.g., menstrual cycles, fertility, pregnancy loss, vitamin D, digital health data and machine learning), as well as to candidates with superior analytic and communication skills.