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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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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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at Genentech (gCS). The group develops and applies state-of-the-art ML/AI models to address open questions in genome biology, with the goal of understanding causal mechanisms of disease and facilitating drug
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) organization which uses data, by developing best in class computational methods, and applying them to the most relevant scientific problems across all stages of the pipeline. This position is based within
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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
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strategies that modulate the crosstalk between tumor and immune cells, and develop new image-based screening technologies to identify targets that mediate clinically-relevant cell-cell interactions
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applicant will have an opportunity to work closely with a diverse scientific team that includes microbiologists, immunologists, cell biologists and bioinformaticians. Who You Are: Recent PhD in the field
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results in a clear and concise manner to a diverse audience of scientists. Who You Are: PhD in Bioinformatics, Computational Biology, Neuroscience, Immunology or related field with deep basic
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Genentech Postdoctoral Program and unlock your full potential! The expected salary range for this position based on the primary location of South San Francisco California is $98,000 to $104,500. Actual pay
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expertise, and creatively take initiative to see your ideas implemented. Able to perform at a high level in a fast changing and demanding environment. The expected salary range for this position based