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Open Postdoctoral position, faculty mentor Pascal Geldsetzer

Important Info

Faculty Sponsor (Last, First Name): 
Geldsetzer, Pascal
Stanford Departments and Centers: 
Med: Primary Care and Population Health
Epidemiology and Population Health
Med: PCOR
Med: Biomedical Informatics Research (BMIR)
Biomedical Data Sciences
Health Policy
Postdoc Appointment Term: 
Flexible
Appointment Start Date: 
Flexible
Group or Departmental Website: 
https://profiles.stanford.edu/pascal-geldsetzer
How to Submit Application Materials: 

Please send a CV (no cover letter or letters of reference required) by email to pgeldsetzer@stanford.edu.

Does this position pay above the required minimum?: 
Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.
Pay Range: 
72,000 - 140,000

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 shingles vaccination and dementia (see: https://www.medrxiv.org/content/10.1101/2023.05.23.23290253v1; and https://www.medrxiv.org/content/10.1101/2023.09.08.23295225v1)
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. Part-time and remote working options are possible; on-site at Stanford or Heidelberg are of course welcome, too.
This is a two-year position with strong possibility of renewal.

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: 

Please send a CV (no cover letter or letters of reference required) by email to pgeldsetzer@stanford.edu.

 

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.