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As of Sep 9, 2026, the average hourly pay for machine learning psychology postdoc in the United States is $22.95, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $25.48 per hour, depending on experience, location, and employer.

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Infographic showing various Machine Learning Psychology Postdoc job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $47,731 per year, or $22.9 per hour.

Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI

Cambridge, MA • On-site

Harvard University
Colleges, Universities, and Professional Schools • 51 - 200 employees
Learn more about Harvard Universityexternal

$75K/yr

Full-time

Re-posted 21 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

83rd of 633 rated colleges and universities

Job description

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 Email
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

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