Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI

Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI at Harvard University Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI at Harvard University in Cambridge, Massachusetts Posted in 11 days ago.

Job Description:

Harvard University Position Details Title Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI 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. Additional Qualifications 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. Contact Information Rui Duan, Associate Professor, Department of Biostatistics Contact rduan@hsph.harvard.edu Salary Range $75,000 Minimum Number of References Required 3 Maximum Number of References Allowed Keywords biostatistics; AI; biomedical informatics; statistics; genetics EEO/Non-Discrimination Commitment Statement 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 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 . 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. Supplemental Questions Required fields are indicated with an asterisk (•). Applicant Documents Required Documents Curriculum Vitae Cover Letter Optional Documents Equal employment opportunity, including veterans and individuals with disabilities. PI284226700