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approaches to large-scale biomedical data. Research topics may include foundation models for longitudinal electronic health records and genomics, multimodal learning integrating health records with molecular
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an ambitious researcher with expertise in artificial intelligence, machine learning, or computational statistics, and a demonstrated interest in applications to human genetics and/or population health. We
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early metabolomic disruptions, followed by the genetic and biochemical dissection of the mechanisms underlying these alterations. The project takes advantage of recent transcriptomic and imaging data
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, selectivity and phenotype mechanisms directly in primary human cells and employ machine learning methods for data analysis. This includes activity-based profiling, global- and phosphoproteomics and phenotype