412 engineering-computation "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" uni jobs at NIST
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RAP opportunity at National Institute of Standards and Technology NIST Computational Modeling of Progressive Structural Failure and Collapse Location Engineering Laboratory, Materials and
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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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RAP opportunity at National Institute of Standards and Technology NIST Engineering Enzymes for the Biomanufacture of Nucleoside Conjugates Location Material Measurement Laboratory, Biomolecular
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Analytical Technology for Biopharmaceutical Process and Product Characterization NIST only participates in the February and August reviews. Biopharmaceuticals are protein-based therapeutics produced
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RAP opportunity at National Institute of Standards and Technology NIST Computational Investigations of Molecular Interface Formation from the Perspective of Cosolvent Preferential Interactions
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RAP opportunity at National Institute of Standards and Technology NIST Materials Discovery Using Synchrotron Radiation, Machine Learning, and Artifical Intelligence Location Material Measurement
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NIST only participates in the February and August reviews. This opportunity focuses on the development and implementation of liquid chromatography mass spectrometry methods for the quantitation of hormones in biological matrices. Hormones are essential for major developmental and reproductive...
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RAP opportunity at National Institute of Standards and Technology NIST Engineering Atoms for Fundamental Constants and Atomic Data Location Physical Measurement Laboratory, Quantum Measurement
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of film behavior, and stimulus-responsive interfaces and (2) development of new bio- and nanometrology tools. In particular, we creatively harness microfluidic technology, basic microfabrication tools
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, robotics), cyberinfrastructure (e.g., databases, high-performance computing, collaboration tools), and humans (e.g., scientists, engineers, students, managers). The recent interest in Explainable AI (XAI