Harvard University
Postdoctoral Research Fellow - CAUSALab
Harvard University, Providence, Rhode Island, United States,
Position
Title:
Postdoctoral Research Fellow - CAUSALabSchool:
Harvard T.H. Chan School of Public HealthDepartment/Area:
EpidemiologyPosition 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 lab. The CAUSALab launched in 2021 to articulate a growing research portfolio, create synergy with its strategic partners, and provide training on causal inference to the next generation of investigators.
For more information on CAUSALab, please visit:
CAUSALab Website .
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:A doctoral degree in epidemiology, statistics, computer science, or a related quantitative fieldTechnical Requirements:Expert knowledge of R or SASAdditional Qualifications:Excellent writing skillsStrong team player with excellent communication skillsAbility to collaborate within the CAUSALab and beyond the research groupAdditional 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.Contact Information:
For additional questions about the position, please contact Joanna Michalski at
jmichalski@hsph.harvard.edu .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.References:Minimum Number of References Required: 2Maximum Number of References Allowed: 2
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Title:
Postdoctoral Research Fellow - CAUSALabSchool:
Harvard T.H. Chan School of Public HealthDepartment/Area:
EpidemiologyPosition 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 lab. The CAUSALab launched in 2021 to articulate a growing research portfolio, create synergy with its strategic partners, and provide training on causal inference to the next generation of investigators.
For more information on CAUSALab, please visit:
CAUSALab Website .
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:A doctoral degree in epidemiology, statistics, computer science, or a related quantitative fieldTechnical Requirements:Expert knowledge of R or SASAdditional Qualifications:Excellent writing skillsStrong team player with excellent communication skillsAbility to collaborate within the CAUSALab and beyond the research groupAdditional 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.Contact Information:
For additional questions about the position, please contact Joanna Michalski at
jmichalski@hsph.harvard.edu .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.References:Minimum Number of References Required: 2Maximum Number of References Allowed: 2
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