181 computer-programmer-"https:"-"https:"-"https:"-"https:"-"HFML-FELIX" positions at NIST
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We develop and utilize state-of-the-art experimental and computational techniques to acquire, evaluate, and correlate thermodynamic data of standard reference quality with a particular emphasis on
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center. Applicants are expected to be skilled in one of the programming language such as C++/C, Perl, Matlab, or R, and have majored in Chemistry, Statistics, or Computer Science. Reference Yang X, et al
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access to. Qualified candidates will have a background in electron microscopy or a relevant branch of computer science. key words Scanning transmission electron microscopy; Nanocharacterization; Electron
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NIST only participates in the February and August reviews. The design and operation of sustainable buildings face multiple challenges to meet energy efficiency, indoor air quality and other potentially competing performance goals. Achieving these goals requires the development and application of...
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RAP opportunity at National Institute of Standards and Technology NIST Combining Theory, Simulation, Machine Learning, and Autonomous Experiments for Industrial Formulation Discovery Location Material Measurement Laboratory, Materials Science and Engineering Division opportunity...
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for achieving recovery-based objectives, (3) computing the collapse risk of new and existing buildings and infrastructure systems, (3) developing improved nonlinear modeling capabilities to evaluate the response
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RAP opportunity at National Institute of Standards and Technology NIST Identifying Material Behavior from Measurements and Simulations in Advanced Mechanical Testing Location Material Measurement Laboratory, Materials Science and Engineering Division opportunity location 50.64.21.C0832...
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; Electron microscopy; X-ray diffraction; X-ray computed tomography; Mechanical properties; Fatigue; Fracture; Modeling; Atom probe; Microstructure; Processing; Eligibility citizenship Open to U.S. citizens
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-based and data-driven prediction models are often impractical for operational use due to unrealistic assumptions, limited data availability, and prohibitive computational costs. To address
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-process densification. Complementary computational model simulation capabilities are also available. [1] J. Ilavsky, F. Zhang, R.N. Andrews, I. Kuzmenko, P.R. Jemian, L.E. Levine & A.J. Allen; J. Appl