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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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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 Integrating Data and Computational Tools for Advanced Materials Design Location Material Measurement Laboratory, Materials
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computer vision and machine learning. Our computational methods development has three primary goals. The first goal is continued support of expert-driven biomolecular structure determination by NMR, with
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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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care vision would involve the merging of technological advancements in several threads computing, imaging, and information technology; health care practice; and health care technology. We are interested
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based on the following topics of interest: Relationships between powder characteristics, process metrics, and final part quality. In-process machine-vision applications for real-time assessment of powder
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, robotics), cyberinfrastructure (e.g., databases, high-performance computing, collaboration tools), and humans (e.g., scientists, engineers, students, managers). The recent interest in Explainable AI (XAI
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tested in the research community which include highly novel methods such as melt pool emission thermography or spectroscopy, structured light projection or other machine vision applications, acoustic