Postdoc - Deep Learning and Pathology


University of California, San Francisco


San Francisco , California

Principal Investigator

Michael Keiser


Submit CV and three letters of reference directly to Please reference “postdoc-dnn-pathology.”


We’re looking for highly motivated postdoctoral candidates with a background in machine learning, pathology, biomedical image analysis, or related fields. The candidate would define or join a deep learning research project compatible with lab directions in neuropathology, dermatopathology, ophthalmic pathology, or by building on ongoing clinical collaborations. These may include molecular pathology, when feasible in the collaboration. Broad themes across these application domains include model interpretability and representation learning.


Python data science expertise required. Desired skills include experience with PyTorch, pandas, OpenCV, and sklearn, or the demonstrated ability to acquire this expertise in a timely manner. Expertise with containers (e.g., NGC, singularity), AI-ops (e.g., CI/CD for ML), rapid caching, performant data formats (e.g., zarr), and/or distributed dataset/model analysis is a plus.

A productive track record with at least one first-author publication is required. We seek a driven individual who will lead her/his research independently and communicate frequently and clearly to the field.