We are seeking a postdoctoral researcher with a focus on developing statistical, machine learning, and causal inferential methods with applications in health care. The postdoc will collaborate on projects of mutual interest with Emily Fox, Professor of Computer Science and Statistics; Ramesh Johari, Professor of Management Science and Engineering; David Scheinker, Clinical Professor of Pediatric Endocrinology and Director of Systems Utilization Research for Stanford Medicine (SURF); and Vasilis Syrgkanis, Assistant Professor of Management Science and Engineering.
Areas of research focus may include:
- Physiologically-grounded modeling, forecasting, and counterfactual prediction for glucose dynamics
- Estimation of treatment effects of policies for care management
- Policy optimization and personalization of policies for care management
- Clinic-level resource allocation
- Design of clinician-facing dashboards and patient-facing messaging to support care
Our unique collaboration between engineers, statisticians, computer scientists, and clinicians provides a rare, exciting opportunity to develop methods that will directly contribute to improvements in patient care. The postdoc will become part of a research team supporting this work that includes clinicians at Stanford Children’s Health and Children’s Mercy Hospital at Kansas City. Part of the effort will include translation of research findings to clinical practice as appropriate.
The postdoc will be expected to help define the research questions of interest, and lead both empirical and methodological research efforts towards publication in concert with students and clinical collaborators. Teaching is not required as part of this position.
- Strong mathematical background, including expertise in one or more of the following areas machine learning, statistics, and causal inference
- Ph.D. (or expected completion by Fall 2024) in computer science, statistics, operations research, or related fields
- Prior experience working with data, including expertise with computational methods and appropriate software platforms
- An interest in translational research with applications in health care
- A description of why you are a good fit for the position
- Current CV
- One representative publication or working paper
- Contact information for two references
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.
