220 computer-programmer-"https:"-"Inserm" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" uni jobs at NIST
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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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RAP opportunity at National Institute of Standards and Technology NIST Computational Electromagnetics Location Information Technology Laboratory, Applied and Computational Mathematics Division
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dielectric films deposited on graphene using a non-contact microwave technique ( https://dx.doi.org/10.1021/acs.jpcb.9b11622) and monolayer graphene ( https://dx.doi.org/10.1021/acs.jpcb.9b11622 ) as a
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controls. The position will require programming skills, mostly with Python. To understand the vision of beamline operations inspiring this opportunity, see these two recent publications: https://doi.org
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industries and research sectors. Our research group is interdisciplinary, drawing from diverse previous research experiences including wet-lab and computational work. Interested candidates are invited to reach
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NIST only participates in the February and August reviews. Computer-based tools, including the NIST Alternatives for Resilient Communities model, or NIST ARC, are being developed to support
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-throughput characterization methods include spectroscopy, optical and scanned probe microscopy, scattering, reflectivity, ellipsometry, and contact angle measurements. See http://www.nist.gov/mml/polymers
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Research." Metabolites 9(7). 3 - https://doi.org/10.6028/NIST.IR.8451 Researchers: Aaron Urbas (aaron.urbas@nist.gov ), Sandra Da Silva (sandra.dasilva@nist.gov ), Ben Place (benjamin.place@nist.gov ) and
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Physics Letters 580: 120, 2013 Nanoporous materials; CO2 capture; Gas adsorption; Metal-organic frameworks; DFT; Theory and modeling; Computational thermodynamics;
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-and-quality-control-materials-metqual-program key words Metabolites; Metabolic pathways; Mass spectrometry; Bioinformatics; Chemometrics; Multivariate statistics; Human health; Precision medicine