Postdoctoral position - Causal inference in electronic health record data
Heidelberg University
Heidelberg Institute of Global Health
We are 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 the Geldsetzer lab expand its work on the link between infections and vaccination, and dementia (see: https://www.medrxiv.org/content/10.1101/2023.05.23.23290253v1). 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.
Remote and part-time work options are possible.
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.
Required Application Materials:
- CV (a cover letter is not required)