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Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI
Harvard University
Details
Posted: 24-Oct-25
Location: Cambridge, Massachusetts
Internal Number: 15425
School: Harvard T.H. Chan School of Public Health
Department/Area: Biostatistics
Position Description:
The Department of Biostatistics at the Harvard T.H. Chan School of Public Health invites applications for a Postdoctoral Research Fellow position in statistics, genetics, and biomedical AI. The lab develops cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and computational challenges arising in precision medicine, mental health, and biomedical informatics.
The postdoctoral fellow will contribute to projects focused on:
- Foundation and representation learning for multimodal biomedical data, including electronic health records (EHRs), genomics, imaging, and clinical text to power next-generation precision medicine.
- Statistical and computational genomics across diverse populations and biobanks for risk prediction, genetic discovery, and genomic medicine.
- Federated and transfer learning for distributed and privacy-preserving data integration.
- AI and Deep learning approaches to high-dimensional and multi-modal biomedical data.
- Causal Inference, Fairness, and Trustworthy AI in real-world healthcare applications.
Our group actively collaborates with large national and international initiatives, including Mass General Brigham, Penn Medicine, Cambridge Health Alliance, PsycheMERGE Network, PCORnet, and OHDSI, providing unique opportunities to work with massive EHR-genomic datasets and multi-site real-world evidence networks.
Basic Qualifications:
- Ph.D. in Statistics, Biostatistics, Computer Science, Statistical Genetics, or a related quantitative field (by the time of appointment).
- Strong background in statistical or machine learning methodology, optimization, or high-dimensional data analysis.
- Proficiency in R or Python; experience with deep learning, causal inference, or genetic data analysis is not required but encouraged.
- Excellent written and verbal communication skills.
Contact Information:
Rui Duan, Associate Professor, Department of Biostatistics
Contact Email: rduan@hsph.harvard.edu
Special Instructions:
The position is available immediately. The initial appointment is for one year, renewable based on performance and funding. Salary and benefits follow NIH and Harvard guidelines.
Interested applicants should submit a CV, cover letter, and contact information for three references to Dr. Rui Duan (rduan@hsph.harvard.edu). Review of applications will begin immediately and continue until the position is filled.
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.
About Harvard University
Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment of over 20,000 degree candidates, including undergraduate, graduate, and professional students. Harvard has more than 360,000 alumni around the world. The University has twelve degree-granting Schools in addition to the Radcliffe Institute for Advanced Study, offering a truly global education. Established in 1636, Harvard is the oldest institution of higher education in the United States.
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https://careers.ashg.org/jobs/21774562/postdoctoral-research-fellow-in-statistical-machine-learning-and-biomedical-ai
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