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Field
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motivated researcher with a strong background in computational modeling, system identification, and uncertainty quantification for civil infrastructure. The successful candidate will join the Risk Assessment
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knowledge of state-of-the-art principles and theories. 5. Develops advanced analytical models and systems and provides solutions and analyses to support strategic and tactical decisions. 6. Adheres
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vulnerability modeling, and (c) population and built environment exposure to climate hazards. The broad agenda of this research is assessing the fitness of geospatial indicators to inform conceptual and policy
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Sciences at Texas A&M University Texas A&M Forest Service Texas A&M Veterinary Medical Diagnostic Laboratory As the nation’s largest most comprehensive agriculture program, Texas A&M AgriLife brings together
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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, Beyond the Standard Model phenomenology, precision calculations for the LHC and intensity frontier, overlaps of particle physics and cosmology, and lattice gauge theory. The lattice efforts span weak
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team. The Research Assistant Professor would lead the lab and be tasked with overseeing the scientific output within the lab, bringing new techniques to the lab (e.g. molecular engineering, informatics
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virological and immune system-based research through long-standing community partnerships and clinical trials research, along with using laboratory models of virus infection. The successful candidate will work
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
, Computational Biology, Information Science or a related field. Required Qualifications, Competencies, and Experience Experience in at least one of the following fields: Large Language Models, Image Processing