Onnela Lab Postdoctoral Research Fellow Position in Network Science/Causal Inference
Listed on 2026-01-10
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Research/Development
Data Scientist -
IT/Tech
Data Scientist
Overview
Onnela Lab Postdoctoral Research Fellow Position in Network Science / Causal Inference
School Harvard T.H. Chan School of Public Health
Department/Area
Position Description
The Onnela Lab in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health is seeking candidates with a Ph.D. in biostatistics, applied mathematics, computer science, or a related quantitative field for a one-year Postdoctoral Research Fellow position. This position involves developing new theory and methods at the intersection of causal inference and network science, building software, and potentially collaborating on applied health sciences projects.
Responsibilities- Develop new theory and methods at the intersection of causal inference and network science.
- Build software and potentially collaborate on applied health sciences projects.
- Basic Qualifications:
Candidates should have a doctoral degree in biostatistics, statistics, or a related field. Strong computational skills and expertise in causal inference or network science are desired but not required. Start date and term are negotiable.
Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes.
Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university’s non-discrimination policy. Harvard’s equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
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