401 Computer-Science-"https:"-"https:"-"https:"-"Data-driven-Materials-Modeling" positions at NIST
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RAP opportunity at National Institute of Standards and Technology NIST Advanced Vibrational Spectroscopy of Higher Order Structures of Protein Location Material Measurement Laboratory
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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 Machine Learning Driven Autonomous Metrology System Location Physical Measurement Laboratory, Sensor Science Division
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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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circuit design and the signal-chain engineering. We will focus on an in-depth analysis of the correlations between the design of the charge circuit and the resulting level of noise and charge sensing
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using them to demonstrate new applications in quantum information science. We have used radio-frequency interferometry to achieve ultra-sensitive high-speed single-photon detection [Applied Physics
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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
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constituent elements, such as H, C, and N (for a general overview see Hoogerheide, D. P., Forsyth, V. T. & Brown, K. A. 2020. Neutron scattering for structural biology. Phys Today73, 36–42). In combination with
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catalytic turnover. Integrative modeling and machine learning have the promise of establishing new tools for combining computational and experimental data from HDX-MS and NMR to explain the dynamics and
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, internal dynamics, materials physics and chemistry is of primary importance in determining the processing, performance and viability of advanced ceramic components such as relevant to solid oxide or hydrogen