413 computer-science-quantum-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ" positions at NIST in United States
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-adoption, etc). A successful applicant would have the opportunity to lead research workstreams, write papers, and engage with AI and measurement science experts from across CAISI and NIST. The artificial
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RAP opportunity at National Institute of Standards and Technology NIST Combining Theory, Simulation, Machine Learning, and Autonomous Experiments for Industrial Formulation Discovery Location
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RAP opportunity at National Institute of Standards and Technology NIST Chemical Metrology of Cannabis Plants and Cannabis-Containing Commercial Products Location Material Measurement Laboratory
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RAP opportunity at National Institute of Standards and Technology NIST Developing Novel Adaptive Molecular Crystals for Gas Adsorption and Storage Location NIST Center for Neutron Research
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RAP opportunity at National Institute of Standards and Technology NIST Compressive Sensing Methods for Electron Microscopy and Microanalysis Location Material Measurement Laboratory, Materials
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on multiple scales, ranging from continuum and empirical molecular mechanics models to first-principles quantum chemistry, often fall short for complementary reasons: the various intermolecular interactions
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characterization, microstructural analysis, modeling, and/or data science to reach out and apply, as a variety of perspectives will be invaluable in advancing our understanding of material behavior and design. We
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Metrology for Quasi-Optical Wireless Probing of Monolithic Microwave Integrated Circuits NIST only participates in the February and August reviews. Ultrafast electronic devices with fundamental operating frequencies above 100 GHz are used in a wide variety of applications—examples include radio...
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RAP opportunity at National Institute of Standards and Technology NIST Experimental Thermodynamic Properties of Fluids Location Material Measurement Laboratory, Applied Chemicals and Materials
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-based and data-driven prediction models are often impractical for operational use due to unrealistic assumptions, limited data availability, and prohibitive computational costs. To address