↳Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field. Candidates with MSc in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field, with 4+ years of relevant industry experience will also be considered.
↳Strong experience analyzing pathology imaging modalities including H&E, IHC, multiplex IF, and / or spatial transcriptomics data.
↳Understanding of machine learning methods for segmentation, classification, detection, and representation learning.
↳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.
↳Strong communication and collaboration skills with the ability to communicate complex data insights and recommendations to cross-functional teams.
↳Strong research skills, evidenced by publications in leading scientific journals and / or conference presentations.
