25 postdoc-in-thermal-network-of-the-physical-building Postdoctoral positions at University of Virginia
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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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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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Collaborate with leading researchers within and outside UVA Qualifications: U.S. citizenship required Ph.D. in Data Science, Statistics, Computer Science, Network Science, Physics, Engineering, Sociology
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for three professional references Applications that do not contain all required documents will not receive full consideration. Questions relating to the application process should be directed to Jeremy
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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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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
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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
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manuscript generation. This position will complete duties as follows: Partnership building and data collection Coordinating with professional learning organizations to ensure consistency data collection
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their communications Data Collection and Analysis: Collect data on the implementation process, including facilitator performance and participant feedback Analyze fidelity data to identify areas where