- A doctoral degree in epidemiology, statistics, computer science, or a related quantitative field
- Expert knowledge of R or SAS
- Excellent writing skills
- Strong team player with excellent communication skills
- An ability collaborate within the CAUSALab and beyond the research group
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Postdoctoral Research Fellow - Cambridge, United States - Harvard University
Description
DetailsTitle Postdoctoral Research Fellow - CAUSALab
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.
Applications span different health areas, but the CAUSALab will prioritize applications for postdocs who will work on cancer or Mendelian randomization.
Basic QualificationsEducation Requirements
Preferred Skills
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 InstructionsOptional 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.
Maximum Number of References Allowed 2
Keywords
Supplemental Questions