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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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scanning (TLS), throughout hardwood-dominated locations in Virginia, including several Department of War installations and bases and large sections of the George Washington-Jefferson National Forest (2
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characterization. The successful candidate will contribute to an externally funded research program focused on understanding structure-performance relationships in molybdenum-based zeolite catalysts for methane
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. • Possess molecular virology or protein biology skills. • Should be enthusiastic and dedicated, have the ability and interest in learning new techniques; must be able to follow verbal and written instructions
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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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, mammalian cell culture, and flow cytometry • Experience with CRISPR-based genome editing • Self-motivated, creative, and detail-oriented • Excellent organizational and time-management skills • Excellent
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in areas related to quantum information theory, quantum error correction, and machine learning. The position will start in fall 2026 and will be for two years, with a possible 1-year extension pending
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and optimization of measurement-based quantum computing protocols for quantum simulation of quantum many-body models. Preference will be given to candidates familiar with the stabilizer formalism and
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research into Hypersonic phenomenon. This position is based at Virginia Tech's main campus in Blacksburg, VA. Specific tasks include designing and leading wind tunnel experiments into hypersonic phenomenon