Postdoctoral Researcher: Causal effect estimation

The team led by Pascal Geldsetzer at Stanford University is looking for a talented researcher with experience in econometric/quasi-experimental approaches for causal effect estimation (e.g., regression discontinuity and difference-in-differences) to help us expand our work on the link between shingles vaccination and dementia/ cognition (see: https://www.nature.com/articles/s41586-025-08800-x; https://jamanetwork.com/journals/jama/fullarticle/2833335), as well as the relationship between vaccines, infections, and dementia more generally.

Data sources for our work in this area are large-scale electronic health record data, medical claims data, mortality registries, and epidemiological cohort studies. The researcher will be expected to publish in high-impact general science and clinical journals.

We are looking for someone to start as soon as possible but there is no specific deadline for the application – we hire on an ongoing basis. We also partner with Heidelberg University for candidates interested in being based in Germany. Remote working options are possible; on-site at Stanford or Heidelberg are of course welcome, too.

Required Qualifications:

• Doctoral degree with quantitative training (ideally in econometrics) or relevant research experience.
• Strong coding skills in R, Stata, or other statistical software package.
• Good communication skills in English.

This is a two-year position with strong possibility of renewal. We also offer attractive opportunities for those interested in a longer-term career in academia that is not on a faculty tenure track.

Application Instructions: Please send a CV (no cover letter or letters of reference required) by email to pgeldsetzer@stanford.edu. Please only apply if you would seriously consider this opportunity.