83 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"St" positions at NIST
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RAP opportunity at National Institute of Standards and Technology NIST Development of New Computational Methodologies for Molecular Simulation of Soft Materials Location Material Measurement
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RAP opportunity at National Institute of Standards and Technology NIST Computational Studies of Functional Oxide Materials and Devices Location Material Measurement Laboratory, Materials
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RAP opportunity at National Institute of Standards and Technology NIST Computational and Theoretical Approaches for Understanding Complex Fluids Location Material Measurement Laboratory
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NIST only participates in the February and August reviews. The Applied Systems team at the Center for AI Standards and Innovation leverages multidisciplinary methodologies to assess, evaluate, and measure AI systems in application and real-world settings to accelerate trustworthy innovation,...
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RAP opportunity at National Institute of Standards and Technology NIST High-performance Computing and Data Visualization for the NIST Fire Dynamics Simulator Location Engineering Laboratory
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NIST only participates in the February and August reviews. As of today, there is a plethora of cyber-physical instruments consisting of physical sensing (e.g., microscopy imaging) and cyber (digital) Artificial Intelligence (AI)-based predictions. These instruments raise concerns about safety...
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of the constraints on sequencing (read length, depth), and informatics (e.g., database composition, algorithm biases). Proposals should address these challenges with strategies to evaluate the metagenomic
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of structural responses. References Wong KKF, Speicher MS: “Improved Method for the Calculation of Plastic Rotation of Moment-Resisting Framed Structures for Nonlinear Static and Dynamic Analysis”. Computational
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NIST only participates in the February and August reviews. This program involves multimodal imaging techniques that use magnetic resonance imaging (MRI) as either a base or as a complimentary
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catalytic turnover. Integrative modeling and machine learning have the promise of establishing new tools for combining computational and experimental data from HDX-MS and NMR to explain the dynamics and