Postdoctoral Associate

Postdoctoral Associate

Work Arrangement:
Hybrid (On-Site and Remote mix)

Location:

Durham, NC, US, 27710 Personnel Area: MEDICAL CENTER

School of Medicine Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe.

Composed of more than 2,500 faculty physicians and researchers, more than 1,300 students, and more than 6,000 staff, the Duke University School of Medicine along with the Duke University School of Nursing, Duke University Health System and the Private Diagnostic Clinic (PDC) comprise Duke Health. a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Primary Care, Duke Home and Hospice, Duke Health and Wellness, and multiple affiliations.

Be You. The REGAL (Research to Eliminate GlobAL Cancer Disparities) team at Duke University invites applications for a Postdoctoral Research Associate to join a rigorous, data-intensive research program focused on advancing cancer health equity in the U.S. and globally. This position is designed for scientists with strong computational and quantitative training who are eager to apply advanced epidemiologic and biostatistical methods to complex, multi-level data.

The Postdoctoral Associate will train under the primary mentorship of Dr. Tomi Akinyemiju, with additional support from junior faculty and senior postdoctoral fellows, within a highly collaborative and methodologically driven research environment. The position emphasizes the development and application of advanced analytical approaches to address fundamental questions in cancer disparities, while building a strong foundation for an independent research trajectory.

REGAL is a multidisciplinary research program integrating social epidemiology, molecular epidemiology, and global health to investigate the drivers of cancer disparities across the prevention and survivorship continuum. Our work leverages large-scale cohort studies, registry data, and multi-omics platforms to generate actionable, high-impact insights. The team operates at the intersection of epidemiologic theory, quantitative methods, and translational science, with a strong emphasis on rigorous study design, reproducible analytics, and integration of biological and social data.

Minimum Requirements:

A PhD degree is required.

Preferred Qualifications:

Experience with large-scale or high-dimensional datasets (e.g., cohort, registry, or omics data) Familiarity with causal inference methods or machine learning approaches Demonstrated experience in scientific writing and publication

Ideal for candidates who:
Have recently completed (or are near completion of) a doctoral degree in Epidemiology, Biostatistics, or a closely related quantitative field Demonstrate strong computational and statistical training, including experience with complex data analysis Have proficiency in statistical programming (e.g., R, SAS, STATA, or Python) Have interest or experience in cancer epidemiology, genomics, and/or social determinants of health Exhibit strong critical thinking, attention to detail, and a commitment to rigorous, reproducible science Are highly motivated, curious, and committed to developing advanced methodological expertise

Quantitative & Computational Analysis:
The Postdoctoral Associate will contribute to the design and execution of analyses addressing cancer disparities using complex, high-dimensional data. This includes implementing advanced statistical and computational methods across diverse data sources such as prospective cohorts, registry datasets, and multi-omics platforms. The role requires strong proficiency in statistical programming, careful attention to analytic assumptions, and the ability to develop reproducible, well-documented workflows.

Methodological Development:
The Postdoctoral Associate will further develop expertise in advanced epidemiologic and biostatistical methods, including causal inference, survival and longitudinal modeling, and approaches for integrating multi-level and high-dimensional data. There will be opportunities to apply and extend machine learning and data-driven methods, particularly in settings that require combining biological, clinical, and social determinants of health. The position emphasizes strengthening both technical depth and methodological rigor.

Research Design & Interpretation:
The Postdoctoral Associate will contribute to the development of research questions and analytic strategies that align with the conceptual and methodological goals of the program. This includes critically evaluating study design,…