About this role
There is a Postdoctoral Fellow – Machine Learning-Enabled Pathology (Yu Lab) vacancy at Harvard University in Boston, United States, working on-site. The role sits in Artificial Intelligence & Data, which shapes the kind of work involved. Working hours are spent in the Boston office, not remotely. The role is pitched at mid-level, so that is the experience band the employer has in mind. The employer's own description further down the page has the rest, including the application link.
Your Career Hunter matched this listing against the employer's careers page on Nov 13, 2026.
Job Overview
Job description provided by Harvard University.
The Department of Biomedical Informatics at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Fellow with experience in machine learning and scientific programming.
The fellow will work with a multidisciplinary team of bioinformaticians, pathologists, oncologists, and computer scientists on original research in computational pathology.
The work focuses on building and applying automated analytical pipelines for pathology data, including histopathology images and multi-omics information such as genomics, epigenomics, transcriptomics, and proteomics.
Digital pathology images hold rich information on complex diseases, and the lab's goal is to turn that information into methods that advance understanding and care.
The fellow will develop and refine machine learning methods for analysing histopathology, clinical, and multi-omics data, and collaborate with the multidisciplinary team throughout.
Findings will be published, with the fellow contributing to the lab's research output alongside colleagues across disciplines.
Applicants need a PhD in biomedical informatics, computational biology, computer science, or a related field.
Substantial experience in machine learning and Python and R programming is essential, along with familiarity with deep learning packages such as TensorFlow, Keras, or PyTorch.
Strong problem-solving and communication skills are highly desirable for this opportunity.
The position is available immediately and can be renewed annually. Applications go by email to Kun-Hsing Yu at Kun-Hsing_Yu@hms.harvard.edu, with a CV, two representative papers, and contact details for three references.