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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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/Responsibilities: The successful candidate will be responsible for conducting, coordinating, and reporting complex research assignments related to energy conversion systems including: Design and develop experimental
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integrating human-in-the-loop reinforcement learning approaches. Responsible AI: Exploration of privacy-preserving AI techniques, enhancing AI safety, and addressing vulnerabilities and defenses in Large
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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. This position resides in the Multiscale Modeling and Materials by Design (M2MD) Group within the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National
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that combines mechanistic ecophysiology with AI, such as: Physics-informed machine learning and neutral networks to investigate plant physiological / abiotic relationships Bayesian statistics and neural and
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-body ab-initio methods for description of electronic, magnetic, and vibrational properties in a range of materials Expertise with artificial intelligence and machine learning approaches will be also
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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and