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interdisciplinary, requiring regular communication between chemists, computer scientists and mathematicians working on modelling these compounds using experimental as well as data from chemistry/physics calculations
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-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements. § Implementing algorithms
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a track record in computational modelling that explores the dynamics of AI systems and the development of autonomous AI agents, experience with machine learning, reinforcement learning, and generative
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Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, and thus requires
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Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires
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(PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must
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on innovative design for legal and regulatory systems for AI and other complex global technologies; computational models of human normative systems; and working with machine learning researchers to build ML
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(PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must
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solutions Design for Scale and Sustainability: Creating system archetypes and generic models that abstract program-specific information into reusable frameworks for future health systems interventions
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to 100 GHz, using custom and commercial test fixtures. Develop and simulate computational models of material-loaded microelectronic devices to quantify electric, acoustic, and piezoelectric fields for a