Mathew Kiang

Stanford University is recruiting one or two postdoctoral scholars for a project on the impact of nonpharmaceutical interventions on COVID-19 outcomes . The work sits at the intersection of causal inference , infectious disease modeling , behavior change , and policy analysis. The primary mentor is Prof. Marc Lipsitch in the Division of Infectious Diseases and Geographic Medicine, Stanford School of Medicine, with co-advising by Dr. Mathew Kiang , Assistant Professor of Epidemiology. The project includes developing a rigorous causal framework for population-level interventions, analyzing state- and county-level U.S. data, and building computational models to simulate COVID-19 transmission under different interventions. The team is especially interested in candidates with experience in causal inference and/or modeling behavior change as a function of policy and external events . Fellows will work closely with experienced infectious disease modelers and cross-train across complementary fields. Eligibility: a PhD in a relevant field is required, including epidemiology, statistics, biostatistics, machine learning, data science, or other quantitative disciplines. Funding: the appointment is for 2 years and pays the Stanford University required minimum for postdoctoral scholars; the FY27 minimum base pay is $79,056 . How to apply: email Marc Lipsitch with a statement of research interests, CV, and contact information for three referees. The postdoctoral office listing provides the official opportunity page and application instructions.