331 parallel-computing-numerical-methods-"Simons-Foundation" positions at NIST in United States
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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 Integrating Data and Computational Tools for Advanced Materials Design Location Material Measurement Laboratory, Materials
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parallel algorithms, execution of algorithms in the computer cloud, to delivering on-demand measurements over the Web. key words Image processing; Machine learning, Computer vision; Statistical methods
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the development towards this end of efficient, highly parallel software running on commodity hardware. Novel methods to compute the stray field from magnetized material with attention to interface and
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Computational Investigation of Flexible Metal-Organic Framework Materials for Gas Storage and Separation NIST only participates in the February and August reviews. Flexible metal-organic frameworks
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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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RAP opportunity at National Institute of Standards and Technology NIST Mathematical Modeling and Simulation Location Information Technology Laboratory, Applied and Computational Mathematics
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challenge to design around. This project will focus on microstructural modeling approaches, including both conventional phase field, phase field crystal; and level set methods, to understand the evolution
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experiments and datasets for model validation of multi-phase computation fluid dynamics (CFD), discrete element method (DEM), or data-driven modelling. Measurement of defect types and populations using micro- x
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augmented intelligent solutions for smart machine tools. For example, new methods may be developed for the monitoring of rotary or linear axes, ball screw preload and backlash, spindle performance, real-time