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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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interacting systems and predict solutions to issues impacting human health, well-being, and habitat. We collaborate across many disciplines to discover connections between health, information networks, security
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to support research presentations, manuscripts, and grant applications. Formulate and define analytic scope and objectives through research and fact-finding as a self-starter. Have a strong motivation to learn
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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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university partners on systems-level issues. Run advanced quantitative analyses using statistical software. Generate research questions for analysis utilizing quantitative and qualitative data collected. Lead
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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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collaborations with investigators outside of UVA and encourage trainees to integrate into this collegial research network. For additional information about the position, please contact Dr. Finan, at finan
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resonance, computed tomography, and echocardiographic images using a wide range of software programs is essential. Additionally, a strong understanding of cardiac anatomy to facilitate image segmentation and
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centered on the history of race, justice, and equity in nursing and healthcare. With the aim of building professional research networks and community, the Fellow may choose to connect with one of the many