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Open Postdoctoral position, faculty mentor Summer Han

Important Info

Faculty Sponsor (Last, First Name): 
Han, Summer
Stanford Departments and Centers: 
Med: Biomedical Informatics Research (BMIR)
Epidemiology and Population Health
Biomedical Data Sciences
Postdoc Appointment Term: 
2-year (can be extended)
Appointment Start Date: 
September 1, 2024 (Flexible)
How to Submit Application Materials: 

Please email the required application materials to: Summer Han, Ph.D. (, Associate Professor of Medicine, Neurosurgery, and Epidemiology, Quantitative Sciences Unit, Stanford Center for Biomedical Informatics Research (BMIR), Stanford University School of Medicine

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: 
$75,000 - $80,000

Postdoctoral fellows in cancer epidemiology to conduct real-world evidence studies in oncology using causal inference methods to examine efficient surveillance and treatment strategies using an integrated database of electronic health records from multiple healthcare systems.
Applications are invited for a postdoctoral fellow position in cancer epidemiology to join Dr. Summer Han’s research group in the Stanford Center for Biomedical Informatics Research at Stanford University. This position emphasizes conducting real-world evidence studies using various causal inference methods (e.g., target trial emulation) to examine efficient cancer screening, surveillance, and treatment strategies using an integrated database of the electronic health records from Stanford Healthcare and Sutter Health, which are linked to the California Cancer Registry, as part of the national SEER registries. The postdoc fellow will work closely with statisticians, computer scientists, oncologists, and epidemiologists in the lab and in other collaborating labs at Stanford to tackle emerging clinical questions in oncology, utilizing various AI methods, predictive modeling approaches, and large language models. Specific areas of interest include but are not limited to (1) electronic health records, (2) causal inference, (3) natural language processing and large language models, (4) generative AI, (5) dynamic risk prediction modeling for high-dimensional survival data using longitudinal features, and (6) machine learning and deep learning for analyzing time-to-event outcomes, or (7) radiomics and medical imaging analysis.

Required Qualifications: 
  • We seek an individual with strong statistical and computing backgrounds.
  • Successful applicants should have a Ph.D. degree in Epidemiology (or biostatistics or related field).
  • Strong programming skill in R is required, and experience in SQL or other databases would be welcome.
Required Application Materials: 
  • Cover letter
  • CV
  • A short description of research interests
  • Contact information of three referees


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.