452 computer-programmer-"https:" "https:" "UNIS" "https:" "https:" "https:" "https:" "Dr" "FCiências" positions at NIST
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addition, the emerging "materials by design" paradigm places emphasis on the use the computation for the development and design of new materials. Candidates with an interest and background in computational
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characterize complex fluids and their interaction with other matters. However, measurements require interpretation that is aided by computational fluid dynamics (CFD) and computational fluid particle dynamics
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-throughput characterization methods include spectroscopy, optical and scanned probe microscopy, scattering, reflectivity, ellipsometry, and contact angle measurements. See http://www.nist.gov/mml/polymers
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Research." Metabolites 9(7). 3 - https://doi.org/10.6028/NIST.IR.8451 Researchers: Aaron Urbas (aaron.urbas@nist.gov ), Sandra Da Silva (sandra.dasilva@nist.gov ), Ben Place (benjamin.place@nist.gov ) and
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absorption fine structure), development of data-analysis approaches and computer software for simultaneous structural refinements using multiple types of data combined with ab initio theoretical modeling
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NIST only participates in the February and August reviews. The Alternative Computing Group at NIST has an ongoing program developing new metrologies to support emerging information processing
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, with raw data accessible from a CDCS database hosted at https://potentials.nist.gov/ . Calculation methods will be integrated into the iprPy calculation framework [1], with source code available
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2178: Baseline Control Systems in the Intelligent Building Agents Laboratory. doi: https://doi.org/10.6028/NIST.TN.2178 . building control; intelligent agents; optimization; data analytics; machine
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NIST only participates in the February and August reviews. The Community Resilience Program (https://www.nist.gov/community-resilience ) is developing science-based tools to assess resilience and
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measurements at 18-digit accuracy using an optical clock network. Nature 591, 564–569 (2021). https://doi.org/10.1038/s41586-021-03253-4 [2] Chave, A. D. (2019). A multitaper spectral estimator for time-series