191 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" uni jobs at NIST in United States
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quantum methods to improve sensitivity of DCS References: https://www.nist.gov/programs-projects/greenhouse-gas-and-atmospheric-trace-gas-measurements Cossel, K. C., Waxman, E. M., Giorgetta, F. R., Cermak
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RAP opportunity at National Institute of Standards and Technology NIST Determination of Structural Ensembles Describing Conformational Averaging in Proteins and RNA from Solution NMR and X-ray
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. This computational approach, incorporating quantum mechanics, can help materials research by a) directly simulating and interpreting experiments, b) establishing relationships between material structure and properties
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Computational Methods for NMR Structural Biology and Biomanufacturing of Protein and Live Cell Therapeutics NIST only participates in the February and August reviews. Protein therapeutics
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. Bandyopadhyay, B. Heer, Additive manufacturing of multi-material structures, Mater. Sci. Eng. R Reports. 129 (2018) 1–16. https://doi.org/10.1016/j.mser.2018.04.001. [2] J. Guo, R. Floyd, S. Lowum, J.-P
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out to discuss potential proposals. (1) https://www.biorxiv.org/content/10.1101/2025.02.18.638308v1.full (2) https://www.nature.com/articles/s41598-024-57981-4 Microbiology; Cell Count; Enumeration
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with 1000× increase in time resolution and 10× improvement in spatial resolution over prototypes. Such an instrument enables to measure the structure of heterogeneous systems including ageing concrete
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of Structured Reinforcement Learning for Supply Air Temperature Control’, presentation at 2022 ASHRAE Annual Conference, June 25-29, 2022, Toronto, ON. Pertzborn, A. J., Veronica, D.A. (2021) NIST Technical Note
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like ion mobility). Applicants are expected to have knowledge of LC-MS/MS. Knowledge of mass spectral libraries would be beneficial. References: https://doi.org/10.1002/rcm.7475; https://doi.org/10.1002
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to increase usage by the community. [1] https://doi.org/10.1039/C9SM01877H [2] https://doi.org/10.1063/1.5123683 [3] https://doi.org/10.6028/jres.123.004 key words Molecular simulation; Monte Carlo