↳PhD (or equivalent doctoral degree) in а relevant scientific discipline, completed prior to the fellowship start date.
↳The program is intended for scientists immediately following their PhD training (graduated in 2026).
↳Demonstrated record of scientific achievement (publications, presentations, patents, or equivalent)
↳Strong commitment to learning, innovation, and professional development
↳Experience analyzing imaging data (e.g. H&E, IHC, multiplex IF, spatial transcriptomics).
↳Experience in one or more of the following areas: generative AI, digital pathology foundation models, geometric deep learning and / or multi-modal learning.
↳Excellent programming skills and proficiency in deep learning frameworks such as PyTorch, with openness to learning new tools and technologies.
