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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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Agentic Retrieval-Augmented Generation (Agentic RAG) architectures, multi-agent systems, and integration of heterogeneous data sources; - Design, development, and integration of Agentic RAG architectures
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Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for excellent and motivated candidates with expertise in Logics for Multi-agent Systems
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a key role in building and integrating of AI agents into gaming scenarios (e.g., gameplay, interactions, procedural content generation, dynamic narratives), and integrating a multimodal detection
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field. Hands-on experience in designing and implementing software systems involving multi-agent frameworks. Familiarity with immersive platform development (e.g., Roblox, Minecraft), including scripting
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stakeholders Track record of scientific creativity and problem-solving in research activities Preferred Qualifications Experience with agentic AI systems, prompt engineering, or multi-agent frameworks
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(http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts
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reinforcement learning, generative learning (e.g., foundational models) applied to multi-agent systems and/or human-AI interaction. Grade 7 salary £45,103 This role is an open-ended contract with a funding end
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 30 days ago
opportunity This role offers an exciting opportunity to develop cutting-edge AI planning and orchestration technologies for Defence logistics, integrating multi-modal agentic AI systems and automated reasoning