332 computational-physics "https:" "https:" "https:" "https:" "LaTIM Brest" positions at NIST
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RAP opportunity at National Institute of Standards and Technology NIST Functionalizing Semiconductor Surfaces Location Physical Measurement Laboratory, Nanoscale Device Characterization Division
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RAP opportunity at National Institute of Standards and Technology NIST Durability of Concrete Materials Containing Reactive Minerals in the Aggregate and Concrete Location Engineering Laboratory, Materials and Structural Systems Division opportunity location 50.73.11.C1032 Gaithersburg,...
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, process, or part qualification and providing benchmarking datasets for model validation to support industry adoption and standards development of metal BJAM. NIST has researched other AM technologies
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on the use of causal Green’s functions (CGF). This technique is referred to as the CGFMD (Causal Green's Function Molecular Dynamics) technique. Presently, we are in the process of generalizing this technique
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RAP opportunity at National Institute of Standards and Technology NIST Drug Toxicity Measurements with Tissues-on-chips and Microphysiologic Systems Location Physical Measurement Laboratory
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NIST only participates in the February and August reviews. The chemical characterization of biomolecules and the measurement of their interactions at low copy numbers are critical for applications in biomanufacturing and personalized medicine. We are developing new electronics techniques that...
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group is working on a dual-track project to expand this class of materials, and the successful candidate will contribute to either the computational discovery or the experimental validation (or both
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RAP opportunity at National Institute of Standards and Technology NIST Autonomous experimentation and machine learning of material properties Location Material Measurement Laboratory, Materials Measurement Science Division opportunity location 50.64.31.C1094 Gaithersburg, MD NIST only...
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Division, where we develop instrumentation beyond the state of the art. Our research program offers a supportive, highly-multidisciplinary environment coupled with outstanding experimental resources
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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