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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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, 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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environment requiring a high level of multi-tasking. Ability to work under pressure and unsupervised required. Ability to obtain Passport Acceptance Agent Certification within one week of start date. Preferred
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intelligent agentic software security architecture. With prior experience in security and AI agents, including prompt engineering, RAG application, multi-agent system, tool use, code analysis and vulnerability
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University of Bologna. Open PhD Position Decision-Making in Proficiency and Risk-Aware Multi-Agent Systems Program: PhD in Electrical, Electronic, and Information Engineering (ETIT), University of Bologna
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, or performance. In this project, the research done by the PhD student will address the interaction layer in a multi-agent systems. It will focus on how to secure interactions can be generated based on emerging and
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TEC. 2. OBJECTIVES: - Review of techniques and work related to Agentic Retrieval-Augmented Generation (Agentic RAG) architectures, multi-agent systems, and the integration of heterogeneous data sources
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, abandonment, comments, peer interaction) Formalization of algorithms for orchestrating educational AI agents : Train RL and LLM agents and study multi-objective optimization (mastery, well-being stability) Work
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. ETRO, the Department of Electronics and Informatics (http://www.etrovub.be/) of the Vrije Universiteit Brussel (VUB), performs fundamental and applied research in signal processing, AI, computer vision
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago
mission development as well as societal applications. The overarching goal of this project is to enhance ISSM’s capability, scalability, and accessibility by developing a multi-modular, agentic AI framework