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expertise in agent-based modelling. The models we build will have an interface with community stakeholders and mobility service providers, so we are particularly seeking applicants who are comfortable in
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. We are looking for a Research Fellow to advance cutting-edge research in multi-agent systems for large language models (LLMs). The role will focus on conducting innovative research in multi-agent
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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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, automation, or autonomous systems. - Dynamic modeling and physical simulation. - Trajectory planning, navigation, or robot control. - Interest in multi-agent systems and human-robot interaction. Technical
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-grade codebases, including data pipelines and analysis workflows. Developing and deploying AI agents and large language model–based tools for tasks such as document processing, information extraction
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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
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
tailored to scientific modeling workflows. Rather than deploying AI as a black-box predictor, we propose a physics-aware AI agent architecture that interfaces directly with ISSM’s modular components
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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