Please email the required application materials to:
Summer Han, Ph.D. (email@example.com)
Associate Professor of Medicine, Neurosurgery, and Epidemiology Quantitative Sciences Unit
Stanford Center for Biomedical Informatics Research (BMIR) Stanford University School of Medicine http://med.stanford.edu/summerhanlab.html
Cancer screening, dynamic risk prediction, causal inference, and health policy modeling
Applications are invited for a postdoctoral fellow position in cancer research to join Dr. Summer Han’s research group in the Stanford Center for Biomedical Informatics Research at Stanford University. This position emphasizes (i) applying novel causal inference methods for analyzing large observational data from electronic health records (EHRs) or administrative claims data (e.g., Medicare) and (ii) evaluating various cancer screening strategies by developing microsimulation models for decision-making in health policy.
Specific areas of interest include but are not limited to (1) cancer screening modeling, (2) microsimulation, (3) decision analysis/health policy modeling, (4) survival data under competing risks, (5) dynamic risk prediction modeling (e.g., landmark model), (6) data integration (EHRs and cancer registries), (7) cost-effectiveness analysis.
- We seek an individual with solid statistical and computing backgrounds
- Successful applicants should have a strong background in biostatistics and cancer epidemiology
- Ph.D. degree in biostatistics, epidemiology (with strong computation skills), or related fields
- Hands-on experience in algorithmic implementation and statistical programming
- Strong programming skill in R is required, and experience in SQL or other databases would be welcome
- A cover letter
- A short description of research interests
- Contact information of three referees