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charter is to do interdisciplinary research across AI hardware, software, and algorithms. AI Accelerators, ML Algorithms, AI Frameworks, and Model-System Codesign have been focus areas in the past - we
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learning algorithms or substantially extending existing ones. Experience with meta-reinforcement learning, in-context learning, or continual reinforcement learning in non-stationary environments. Experience
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algorithms/workflows compatible with the leadership-class high-performance computing facilities available at ORNL and other DOE facilities. Independently plan and conduct simulations while routinely
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