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challenging and impactful research and development programs in healthcare informatics, bioinformatics, high performance computing and deep learning. We have a collaborative environment focusing on designing
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machine learning, deep learning, foundation models, agentic AI systems, graph neural networks, and knowledge‑graph–based reasoning. Familiarity with integrating AI into scientific workflows at scale
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mathematically rigorous approaches to optimize the trade-off between privacy and utility especially in the context of large models. Advance knowledge of key AI methods such as deep learning, algorithm design
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from plant genomics to phenomics with biological mechanisms embedded in deep neutral networks. GPTgp will allow task-specific training and transfer learning across reactions, pathways, biodesigns, and