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Field
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argumentative agentic AI approach for chemical development settings based on reinforcement learning but able to shape rewards with the help of ontological knowledge as well as expert knowledge from humans and
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of cell factory engineering. Develop software tools that enable programmatic interaction between large language model agents and metabolic models, enabling automated simulation, interpretation, and
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environmental simulations in game engines and integrate them into a persistent multi-user environment platform. Develop and refine RAG-based AI agents using Google AI Studio Pro. Manage the workflow of converting
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, and can analogous mechanisms be engineered into multi-agent AI systems? You would answer this question by building and testing computational models, developing multi-agent simulations where agents
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. This position is part of the DOE-BES initiative Integrated Scientific Agentic AI for Catalysis (ISAAC), a multi-facility collaboration integrating experimental measurements, simulations, and data science to
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systems Reinforcement Learning and Agentic Control: Hands-on experience with reinforcement learning, multi-agent systems, or planning-based agents for autonomous vehicles or robots operating in dynamic
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are used to enable systematic comparisons between alternative strategies in simulated environments. The project also studies simulation agents operating within these models, including both policy-based
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are they talking about, what do they want, need, and value? What are they concerned about? What AI techniques and intelligent agents can we develop to work supportively and/or unobtrusively along with them
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bridge the fields of Generative AI, Recommendation System, Labor Economics/Organizational Science, and Social Simulation Platform. The key focus areas of this project include: 1. Agentic Career
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compositions of these materials with potential adsorption properties for simulants of toxic agents or catalytic properties of interest for degradation action, a molecular modeling approach based on density