201 associate-professor-computer-"https:"-"https:"-"https:"-"https:" positions at NIST
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RAP opportunity at National Institute of Standards and Technology NIST Magnetic Resonance in Industrial Applications Location Physical Measurement Laboratory, Applied Physics Division opportunity location 50.68.62.C0945 Boulder, CO NIST only participates in the February and August...
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of prior physics knowledge into the data analysis, including both physics theory and databases of experimental and computational materials property data. We currently run 10 diverse autonomous platforms
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; Combinatorial library; Informatics; High-throughput; Composition spread; Hyperspectral data Analysis; Data mining; Functional materials;
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on the initial crystallographic texture and uniaxial stress-strain data, thereby predicting the evolution of the yield surface in multi-axial tensile space for a real specimen. Computed constitutive models will be
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, are attempting to expedite discovery by applying modern computational methods to identification and characterization of novel material systems. In this context, the NIST/TRC Group is building capabilities in
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measurement platforms using present and next generation electron microscopes. If you are a creative individual and can imagine what “can be” given the data richness of our program, we invite you to apply and
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RAP opportunity at National Institute of Standards and Technology NIST Mathematical Foundations for System Interoperability Location Information Technology Laboratory, Software and Systems Division opportunity location 50.77.51.B7916 Gaithersburg, MD NIST only participates in the February...
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. These small -scale projects offer opportunities across all aspects of an experimental program from simulation to operations and data analysis. key words cold neutrons; cosmology; neutron physics; beta decay
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, physical, optical, and thermal properties of WBG semiconductors, including diamond, make these materials among the most prospective for high-frequency power electronics, quantum computing, solar-blind
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substances in a wide pressure and temperature ranges). We also possess significant computational resources necessary for successful implementation of molecular simulations and machine learning methods