Important Info
Please send materials to PI Dr. Michelle Lin (mplin [at] stanford.edu) with the subject line:
“Postdoctoral Fellowship Application.”
Dr. Michelle Lin's lab in the Department of Emergency Medicine at Stanford University is seeking a highly motivated postdoctoral researcher to lead innovative, NIH-funded research on emergency care delivery, health policy, and health equity. The fellow will lead analyses using Medicare and Medicaid claims to study access, utilization, and outcomes following emergency department (ED) visits—particularly among older adults and populations facing barriers to care.
This position is ideal for candidates with strong quantitative skills and an interest in applying health services research and policy methods to real-world questions in acute and population health.
Key Responsibilities
- Conduct and manage research projects focused on emergency medicine health services, care transitions, and population-level outcomes.
- Utilize advanced quantitative methods to analyze large healthcare datasets, including Medicare and Medicaid claims (MedPAR, Outpatient, Carrier, TAF).
- Develop reproducible code and workflows for data cleaning, linkage, and analysis within Stanford’s secure computing environment.
- Collaborate with multidisciplinary teams of clinicians, economists, and policy researchers.
- Prepare manuscripts, tables, and figures for peer-reviewed publications and national presentations.
- Contribute to grant proposals and mentor trainees as appropriate.
- Engage in professional development, grant-writing, and optional training in implementation or data science.
Appointment Details
- Start date is immediate and contingent on candidate experience, interests, and alignment with the Lin Lab portfolio.
- The fellowship term is 1–2 years, with a preference for candidates able to commit to 2 years.
- Flexible work schedule
Pay Range: $76,383-$115,000
- PhD or equivalent degree in health policy, health services research, epidemiology, biostatistics, public health, or a related quantitative discipline.
- Strong quantitative and analytical skills with proficiency in R, Python, Stata, or SAS.
- Demonstrated experience with large administrative or EHR datasets; experience with Medicare or Medicaid claims strongly preferred.
- Excellent written and verbal communication skills; ability to work independently and collaboratively.
Interested candidates should submit:
- Curriculum Vitae: applicants without a demonstrated experience of independently analyzing complex datasets are unlikely to be a good fit
- One-page statement of research interests and career goals
Applications will be reviewed on a rolling basis until the position is filled. Selected candidates will be asked for a writing sample (e.g., first-author publication or preprint with related analysis code) demonstrating relevant experience and 3 professional references.