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author paper published or accepted in peer-reviewed journals. Computational skills, retinal in vivo experience, or omics experience would be advantageous. Expertise in retinal disease modeling especially
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models to predict TCR-peptide/MHC (pMHC) interactions. Utilizing structural computational biology techniques to characterize and model TCR-pMHC interactions. Designing experiments to test and validate
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computational biology, who works well within a team. Excited about developing and applying cutting-edge ML/AI models to solve open problems in genomics and biology. Preferred Qualifications: Experience with
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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computational colleagues to build, train, and evaluate cutting edge AI models using large proprietary oncology datasets Leverage multimodal high dimensional data to investigate relationship between heterogeneous
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omics, label-free microscopy, in vivo screens, and foundational models. The ideal candidate for this role has a strong foundation in both experimental and computational sciences, but exceptional