Postdoc - Deep Learning and Pathology - University of California, San Francisco

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. Qualifications 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. Environment Just north of Silicon Valley, the lab’s location at UCSF Mission Bay directly adjoins SoMa district and the heart of SF’s tech and artificial intelligence startup scene. How to apply Interested candidates should submit a CV and arrange that three letters of reference be sent directly to . Please reference “postdoc-dnn-pathology”. Related topics Topic list, column headers with buttons are sortable. #J-18808-Ljbffr Image