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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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related field. Demonstrable expertise in foundation models / large language models, multimodal modelling, or agentic / multi-agent systems is essential. Experience or strong knowledge of causal discovery
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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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description of the project] * Background of the recruitment and description of the project The Agentic AI Research Team (AART) is seeking an outstanding postdoctoral researcher specializing in NLP or applied
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-Test-Analyze (DMTA) cycle, infusing scientific automation with foundation models, multi-agent systems, and robotics to make scientific discovery intelligent, autonomous, and fast. We're seeking a
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: Develop data-driven numerical models (opinion models, norm dynamics, multi-agent systems). Network Science: Study social and temporal interaction networks using network physics tools. Simulation: Conduct
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next-generation process automation and enhancing data flow across the supply chain, while demonstrating the value and capabilities of advanced AI and multi-agent systems for the construction industry
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should be exclusively submitted through the consortium webpage https://raptor-consortium.com/recruitment/ RAPTORplus aims at adapting proton therapy treatment with multi-modality image information acquired
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integration, contributing to CSIE’s mission of advancing autonomous multi-agent systems for national defence applications. Key Responsibilities: • Design and develop hardware and software platforms
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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