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Learning (SciML) applied to physical or engineered systems, including deep neural network surrogate modeling, physics-informed neural networks (PINNs), reinforcement learning (RL), transfer learning, dynamic
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-day activities within research teams, develop project independence, publish research, and support grant proposals. Emphasis is given to individuals who can process infectious disease data, build novel
Searches related to complex systems physics
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