Job Listings

Postdoctoral Research Fellow - CAUSALab

Harvard University
Job Location:
Cambridge, 02138
Public and Environmental Health

School: Harvard T.H. Chan School of Public Health

Department/Area: Epidemiology

Position Description

The CAUSALab in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health is accepting applications for postdoctoral research fellows to work on research activities within the research lab. The CAUSALab launched in 2021 to articulate a growing research portfolio, create synergy with it;s strategic partners, and provide training on causal inference to the next generation of investigators.

For more information on CAUSALab, please visit:

The postdoctoral research fellow will work on causal inference projects under the supervision of the CAUSALab's faculty members. The projects range from the development of causal inference and AI methods to the implementation of established causal inference approaches to support public health and clinical decision making. 

Basic Qualifications

Education Requirements
  • A doctoral degree in epidemiology, statistics, computer science, or a related quantitative field
Technical Requirements
  • Expert knowledge of R or SAS

Additional Qualifications

Preferred Skills
  • Excellent writing skills 
  • Strong team player with excellent communication skills 
  • An ability collaborate within the CAUSALab and beyond the research group
Additional Information:Per university payroll tax guidelines all applicants must reside in any of the following states or be willing to relocate to: Massachusetts, New Hampshire, Rhode Island, Connecticut, Maryland, Vermont or New York.

Special Instructions

Optional Writing Sample (strongly recommended)

Contact Information

For additional questions about the position, please contact Joanna Michalski

Contact Email:

Equal Opportunity Employer

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

Minimum Number of References Required: 2

Maximum Number of References Allowed: 2

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