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control, Large-scale or distributed optimization for complex aerospace systems, Machine learning, reduced-order modeling, surrogate modeling, and data-driven approaches with applications to aerospace
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with the Virginia 4-H Program guidelines, the Virginia Department of Education’s Standards of Learning guidelines, and the American Camp Association’s standards for camps and conference centers
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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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to: artificial intelligence, machine learning, supply chain management, finance, healthcare, energy, and/or sustainability. We are seeking candidates motivated to contribute to a collegial, interdisciplinary
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, organizational and time management skills with ability to execute program plans • Proficient computer skills such as email tools, data entry, and manipulating Excel spreadsheets • High comfort level with learning
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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
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, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against
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broad range of research areas. We are interested in an experimentalist who can develop large datasets in support of emerging artificial intelligence and machine learning driven advances in fluid dynamics
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orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants
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pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise