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. Preferred Qualifications • Experience with deep learning architectures applied to geophysical or environmental data. • Familiarity with physics-informed machine learning or hybrid modeling approaches
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candidate will play a key role in developing and advancing new models and simulations for Computational Fluid Dynamics (CFD) hypersonic codes. Specific tasks include developing new turbulence and transition
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Job Description The Unsteady Fluid Mechanics and Acoustics Laboratory in the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech is seeking a postdoctoral researcher in
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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learning, or deep learning models Appointment Type Restricted Salary Information Commensurate with experience Review Date March 10, 2025 Additional Information The successful candidate will be required
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, 2022 ( https://www.nature.com/articles/s41593-022-01109-2 ) The successful candidate will work with mice and conduct in vivo neurophysiology with molecular tools, data analysis, and modeling (using
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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Job Description The PHASE research group within the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech invites applications for a postdoctoral researcher position in
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CRISPRai and optogenetic control systems and developing predictive metabolic models for the oleaginous yeast Yarrowia lipolytica. This position offers a unique opportunity to conduct cutting-edge research
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. - Strong proficiency in machine learning, optimization algorithms, and computational modeling applied to construction systems. - Experience with designing and conducting experimental studies to evaluate