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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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-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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RAP opportunity at National Institute of Standards and Technology NIST Model Polymer Gels and Networks for Rational Sustainable Design Location Material Measurement Laboratory, Materials Science
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driven self-assembly in an effort to elucidate the underlying thermodynamic and kinetic effects that control the speed, yield, and complexity of self-assembled nanostructures. Our research effort involves
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RAP opportunity at National Institute of Standards and Technology NIST First-Principle Based Modeling for Advancing 2D Electronics Location Material Measurement Laboratory, Materials Science and
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Causal Green’s Function for Modeling of Phonon Transport in Nanoscale Semiconductors: Application to Devices for Thermal Management and Energy Applications NIST only participates in the February and
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alloys, carbon-based composites, and solid-state-biomolecule hybrid structures. Our data-driven development uses cheminformatics methodologies combined with machine learning methods to produce predictive
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, and c) predicting new phenomena and discovering improved materials for applications. My efforts in this area use a variety of modeling approaches to answer questions on materials systems of interest
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MultiPhysics Measurements and Modeling for Microelectronics at Microwave and mm-Wave Frequencies NIST only participates in the February and August reviews. Performance, security, and reliability
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Exploring Material Behavior Across Scales: Mechanical Characterization, Microstructural Analysis, FEA/AI/ML Modeling, and Automation Approaches NIST only participates in the February and August