Postdoctoral Fellowship: Pollution and Health

Fellowship Description

This postdoctoral research opportunity may be focused primarily on health outcomes, rigorous controlled research approaches, mechanisms of disease, health care, social disadvantage, and/or disparities.  The postdoctoral research fellow will have the opportunity to collaborate with a variety of population scientists, lab scientists, epidemiologists, clinicians, biostatisticians, and social scientists at Stanford University as well as other institutions. Mentors will include Stanford University faculty working in any area of pollution and/or population health sciences research.

The fellowship will be appointed through the Stanford Center for Population Health Sciences (PHS) and Stanford’s Sean N. Parker Center for Allergy and Asthma. Fellows will have opportunities to be involved with a variety of other leading research centers at Stanford, such as the Quantitative Science Unit (QSU), Center for Innovation in Global Health (CIGH), and the Center for Policy, Outcomes, and Prevention (CPOP).

Funding Details

This fellowship is a two year appointment. Funding includes a living stipend and funds for some research expenses, plus certain medical, dental, vision, and life insurance coverage through Stanford's Postdoctoral Scholars program.

Applicant Requirements

  • Training and experience in epidemiology, basic science, computational biology, clinical trial research, or a related field
  • Familiarity with statistical software, (e.g., SAS, R)
  • Strong training in quantitative epidemiologic methods (e.g., causal inference methods, Bayesian methods)
  • Strong written and interpersonal communication skills
  • Highly motivated to make a difference in pollution and health

NOTE: Applicants need not have completed their doctoral training prior to applying, although training must be completed prior to the start of the fellowship.

Application Process

Interested applicants should submit the following materials:  

  1. Curriculum vitae;
  2. Statement of research interests to be pursued during training;
  3. One lead-author manuscript; and,
  4. An example of your statistical code.