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Field
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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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Requisition Id 16166 Overview: The Programming Systems Group at ORNL seeks a forward‑leaning Postdoctoral Researcher to advance research at the nexus of Agentic AI, high‑productivity programming
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what alignment is required between the world models of agents and humans that collaborate. You also develop communicative strategies for the agent to detect misalignments and take actions to resolve
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based on an individual-centered spatial analysis approach (geomatics) using AgentBased Modeling to model mobility and its evolution. The postdoctoral researcher will intervene in the second phase
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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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Philanthropy and is fixed-term until 31 Dec 2027. A further extension to this would be based on funding availability. You will conduct hands-on empirical research in multi-agent security and agentic AI security
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agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware spectroscopy workflows. The researcher will work closely with a multidisciplinary team of X-ray physicists and
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optimization and LLM alignment: design preference-based training and fine-tuning methods (RLHF, PPO, DPO, reward modeling) for medical and multilingual LLMs. Agentic and tool-augmented AI systems: develop
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Recommendation Systems Build LLM-based agent systems for personalized career recommendation that operate over long-term user memory, structured experience representations, and continual information retrieval
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Philanthropy and is fixed-term until 31 Dec 2027. A further extension to this would be based on funding availability. You will conduct hands-on empirical research in multi-agent security and agentic AI security