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)—topics including, but not limited to: · Physics-informed neural networks (PINN) & neural operators · Physics-aware convolutional neural networks (PARC) · Meta-learning/transfer
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. This position offers a unique opportunity to contribute to high-impact, interdisciplinary research at the intersection of network science, global research competitiveness, and generative AI capabilities
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science of science, network science, and natural language processing. As part of a small research team, the postdoc will help lead efforts to provide a quantitative model of global competitiveness
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disease (CAD). You will apply expertise in data science, machine learning, as well as multi-omics integration to predict and validate functional regulatory networks in vascular cell types. This work will
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within broader gene networks regulating islet autoimmunity. This project involves generating data from longitudinally collected human peripheral blood mononuclear cells at the single-cell level (CITE-seq