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computing (HPC), with an emphasis on developing intelligent systems that can accelerate large-scale scientific research on leadership-class supercomputers. The successful candidate will contribute to research
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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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), custom accelerators, and next-generation quantum and analog devices. Your work will contribute to a vision of autonomous system engineering in which AI agents understand algorithmic intent, architectural
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Gaussian-process emulators for accelerating parameter estimation and uncertainty propagation Selective cross-scale evaluation using complementary ecosystem observations (e.g., experiments) to test how AI
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) to accelerate the characterization of degradation mechanisms in catalysts and electrochemical devices. This position resides in the Applied Microanalysis and Thermophysics (AMAT) Group in the Materials Analysis
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carlo), as well as experience in developing and/or applying advanced AI/ML methods to accelerate materials discovery. The project will involve integrating such theory-informed AI-models for creating