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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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be developing and applying advanced AI models and sophisticated multi-agent systems to address pressing challenges in regulatory genomics. Key research areas include: Mechanisms of Common and Rare
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the Sterne-Weiler Lab i n Computational Biology / Discovery Oncology. The postdoctoral position is focused on developing and applying foundational AI models to investigate clinically relevant cancer
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models with cutting edge molecular techniques to define the pathobiology of respiratory diseases and develop novel therapeutic strategies. The Müller Lab collaboratively designs high-throughput molecular
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and curious Postdoctoral Fellow to develop and drive projects on retinal disease modeling and repair. OPTI is a part of Genentech Research and Early Development (gRED): scientists in gRED
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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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on developing and applying foundational AI models to investigate clinically relevant cancer vulnerabilities and their relationship with molecular context. Spanning functional genomics and large-scale clinical
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that combine the engineering and analytical principles of multiple scientific disciplines. We are seeking a talented postdoctoral fellow to join our team and advance our mission by contributing to the discovery
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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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technologies (single cell, CRISPR, spatial) and microscopy are highly desired. Expertise in spatial-omic (Xenium) data analyses and interpretation is highly desired. Experience with new technology development is