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-fidelity optimization, neural architecture search, or large-scale AutoML systems. Familiarity with surrogate modeling, physics-informed neural networks, or uncertainty quantification for scientific
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& Interface Science Section of the Materials Science and Technology Division (MSTD), Physical Sciences Directorate at Oak Ridge National Laboratory (ORNL). As part of our research team, you will collaborate
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Focus will largely be in developing and deploying such AI/ML algorithms, closely collaborating with theorists and experimentalists to realize physics- models and/or physics-aware ML-models that can bridge
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systems (proteins, enzymes, membranes, and complexes) Integrate AI/ML approaches with physics-based simulations to accelerate discovery and improve predictive fidelity Contribute to cross-scale modeling
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and software tools for visualizing and analyzing materials characterization data Develop novel, data-driven materials characterization workflows Advance understanding of process-structure-property