Postdoctoral Fellowship in Cancer Epidemiology, Causal Inference, and EHR Data Integration

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 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.