182 structures-"https:" "https:" "https:" "https:" "https:" "https:" "Ruhr Universität Bochum" positions at NIST
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RAP opportunity at National Institute of Standards and Technology NIST Investigating Time-dependent or Transient Structures of Complex Soft Matter Materials Driven by External Stimuli Using
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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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aimed at reducing the fire hazard of and exposure of potentially harmful chemicals used in products and materials found in buidling contents and construction, fire fighter gear, and a wide variety of
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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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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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testing novel MOF materials for applications in carbon capture (https://doi.org/10.1016/j.xcrp.2022.101063). Successful candidates must have a background in MOF synthesis and characterization. Special
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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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NIST only participates in the February and August reviews. There is a growing need for high-performance materials for various technological applications. To address this need, the NIST-JARVIS (https
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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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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