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RAP opportunity at National Institute of Standards and Technology NIST Scientific machine learning methods for trustable accelerated materials characterization and design Location Material
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DFT, beyond-DFT, and experimental techniques. We are also interested in developing both forward and inverse machine learning models to accelerate and optimize the design processes. We work in close
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RAP opportunity at National Institute of Standards and Technology NIST Materials Modeling, Characterization, and Design for Plasticity Location Material Measurement Laboratory, Materials Science
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RAP opportunity at National Institute of Standards and Technology NIST Design, Synthesis, and Characterization of Chromatographic Sorbents Location Material Measurement Laboratory, Chemical
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RAP opportunity at National Institute of Standards and Technology NIST Design, Characterization, and Modeling of Sequence Controlled Polymers Location Material Measurement Laboratory, Materials
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to address chronic stressors; and natural or nature-based systems as part of community resilience. Community Resilience and Infrastructure Design. This project has two research focus areas: (a) To advance
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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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RAP opportunity at National Institute of Standards and Technology NIST Improving Efficacy through New Measurements and Classical Design Location Material Measurement Laboratory, Materials
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RAP opportunity at National Institute of Standards and Technology NIST Full-field imaging and data frameworks for impact materials by design Location Material Measurement Laboratory, Materials
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RAP opportunity at National Institute of Standards and Technology NIST Design Principles for Advanced Pluripotent Stem Cell Culture Location Material Measurement Laboratory, Biosystems and