428 computer-science-programming-languages-"St"-"FEMTO-ST-institute"-"St" positions at NIST
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RAP opportunity at National Institute of Standards and Technology NIST Nanoscale Characterization of Photovoltaic Materials and Devices Location Physical Measurement Laboratory, Nanoscale Device
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RAP opportunity at National Institute of Standards and Technology NIST Metabolomic and Lipidomic Research: Emphasizing Advanced Data Analysis, Metabolite/Lipid Annotation, and Functional Pathway
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determined by geometry, microstructure, chemistry, dimensional scale, proximity to other materials, and exposure to external stressors. Integration of powerful characterization techniques and reliability tests
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RAP opportunity at National Institute of Standards and Technology NIST Multimodal Microbiome Measurements Location Material Measurement Laboratory, Chemical Sciences Division opportunity
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of firefighter's to per- and polyfluoroalkyl substances (PFAS) from their gear (FFG): https://www.nist.gov/programs-projects/measurement-science-and-polyfluoroalkyl-substances-pfas Engineered Fire Safe Products
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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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NIST only participates in the February and August reviews. Knowledge of fluid thermophysical properties is vital for applications in industry, metrology, and environment. The tools of statistical mechanics (Monte Carlo or molecular dynamics simulation, calculation of virial coefficients from...
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RAP opportunity at National Institute of Standards and Technology NIST Lightweight Cryptography for Resource Constrained Applications Location Information Technology Laboratory, Computer
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include the development of novel polymeric mechanical testing devices, novel adhesion blister testing devices, development of high-throughput screening devices, informatics, and data base development. key
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; Autonomous; Machine learning; Informatics; High-throughput; Data mining; Functional materials; Active Learning