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. - Strong expertise in multiscale/multiphysics modeling relevant to catalysis, and experience with machine learning models. - Deep understanding of reaction kinetics, thermodynamics, and structure-reactivity
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. deep learning. Experience with at least two of the following: remote sensing of surface and ground water resources, analysis of satellite gravimetry (GRACE) data, analysis of radar and optical remote
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Department of Electrical and Computer Engineering. The Postdoc will particularly participate in the design and development of integrated system-on-chips for wireless sensing, communication, and implantable
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). The PhD must be awarded no more than four years prior to the appointment effective date so that the candidate has the VT required minimum of one year eligibility as a VT Postdoc. - Demonstrated experience
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tailored to their career goals. Postdocs are actively mentored to publish, present, build collaborations, and compete for fellowships and career-development awards (e.g., NIH F32, K99/R00). The position is
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models and machine learning techniques for kinetic equations arising from plasma and neutron transport. The position will be based at Virginia Tech’s campus in Blacksburg, VA. The postdoc will have a
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, College of Engineering as well as the new Virginia Tech’s Institute for Advanced Computing (IAC) located at the Washington DC metro. The position involves conducting research in federated learning, and
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that transforms current AI for Science paradigms focusing on multidisciplinary applications in biomolecular modeling and design, leading to a step-change in Scientific Machine Learning (SciML). They will be
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that can be repurposed for viruses with pandemic potential. This includes working closely with computer scientists to utilize published “omics” datasets and machine learning approaches to identify FDA
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ethic, and enthusiasm for learning as much as prior technical expertise. Note: Candidates with complementary training backgrounds are encouraged to apply if they bring strong motivation to learn new