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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
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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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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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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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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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responsible for preparing and utilizing chemical solutions in in-vitro experiments in a wet lab setting, maintain colonies of mouse models of human disease through husbandry and genotyping. The successful
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work with colleagues from Virginia Tech and other collaborating universities to run, analyze, and model human evacuation experiments. Data will include motion capture and psychophysiology data to explore
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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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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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talks to professional audiences. Required Qualifications - Ph.D. in mathematics or a related discipline at the time of appointment. PhD must be awarded no more than four years prior to the effective date