412 engineering-computation-"https:" "https:" "https:" "https:" "https:" "University of Warwick" positions at NIST
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of Computational Materials Engineering (ICME) in an AI platform for industrial AM production. This research philosophy relies on a dual approach: Data Informatics & Analytics: Leading investigations into the root
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browsing capabilities. A small subset of project relevant publications is listed below. Requirements:A candidate should have at least a master’s degree in computer science or related fields (PhD is preferred
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RAP opportunity at National Institute of Standards and Technology NIST Development of New Computational Methodologies for Molecular Simulation of Soft Materials Location Material Measurement
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RAP opportunity at National Institute of Standards and Technology NIST Modeling Complex Microstructures Location Information Technology Laboratory, Applied and Computational Mathematics Division
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RAP opportunity at National Institute of Standards and Technology NIST Interface Engineering: Using Surface Chemistry to Impart Desired Properties Location Physical Measurement Laboratory
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RAP opportunity at National Institute of Standards and Technology NIST Infrared Technology Location Physical Measurement Laboratory, Sensor Science Division opportunity location 50.68.51.B7540
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RAP opportunity at National Institute of Standards and Technology NIST Computational Electromagnetics Location Information Technology Laboratory, Applied and Computational Mathematics Division
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research in high-impact science and engineering fields that utilize vapors, liquids, and aerosols. Our experimental scientists focus on developing fundamental measurements and novel methodologies that can
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industries and research sectors. Our research group is interdisciplinary, drawing from diverse previous research experiences including wet-lab and computational work. Interested candidates are invited to reach
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reconstruction using Fourier domain optical normalization." Light-Science and Applications 5: el 60389, 2016. http://dx.doi.org/10.1038/Isa.2016.38 Henn MA, et al: "Optimizing the nanoscale quantitative optical