"Post-Doc Research Associate"

Position Summary/Description

Full-time post-doctoral position at the University of North Carolina at Chapel Hill in the Lineberger Comprehensive Cancer Center. We are looking for candidates interested in developing expertise in tobacco control policy research and systems science. The position is part of the UNC NIH/FDA-funded Tobacco Center of Regulatory Science (TCORS). The broad theme of the UNC TCORS is building the science for effective FDA public health decision-making about tobacco products.

The specific project the postdoc will work on uses microsimulation modeling to estimate the public health impact of a ban on flavored cigars in different plausible post-ban scenarios in the US population. A key goal of this project is to understand how contextual factors, such as retailer compliance or policy enforcement, may impact ban effectiveness.

This mixed-methods project includes use of nationally representative surveys, literature reviews, causal loop diagramming, an expert elicitation process, and simulation modeling. The postdoc will take part in study design, implementation, data analysis, and interpretation and publication of study findings. The postdoc will also develop their own research questions regarding tobacco regulatory science and will receive multidisciplinary training and mentorship from senior researchers with expertise in tobacco control and systems science. Prior experience with decision science, tobacco control or simulation modeling is preferred, but not required.

Along with other tobacco control trainees at UNC, postdocs will be able to participate in career development webinars. In addition, travel funds will be available to present research.

Initial appointment is for one year with additional one-year appointments for up to a total of two years. The preferred start date of the position is January 2026.

Education and Experience

Excellent written and verbal communication. Experience with writing and publishing scientific research papers. Experience with qualitative methods or quantitative research methods, including statistical analyses and stakeholder engagement. Experience with systems science methods such as simulation modeling is preferred.