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Reform. This NSF-funded (#2142873) project investigates the extent to which a change agent can influence reform in chemistry doctoral programs. The postdoc will be involved in designing programming
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the form of, for example, agentic systems or other abstract AI-pipelines, but research has shown that existing frameworks are brittle. If successful, though, such systems can uncover high-value insights from
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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