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foundation models and agentic AI models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi
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integrate the use of Large Language Models (LLMs), LLM agent, Agentic AI models and automated reasoning approaches for the interpretation of complex data, the analysis of experimental protocols, and the
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, physical limitations). Their activities will include: - Design and analysis of mathematical models of multi-agent systems, with an emphasis on stability, controllability, and synchronization. - Obtaining
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• Familiarity with LLM in-context learning and prompt engineering • Basic understanding of modern LLM models, ecosystems, and pipelines, including retrieval-augmented generation, tools/chains, and LLM agents
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agents. The major functions of this position are to conduct experiments and to organize the laboratory. Duties will include: use of murine models of oropharyngeal candidiasis and of voluntary ethanol
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pipeline of ideas to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses, drugs, antibodies, human lymph system, seconds, days
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) department at Telecom Paris. Reinforcement learning (RL) has emerged as a useful paradigm for training agents to perform complex tasks. Model-based RL (MBRL), in particular, promises greater sample efficiency
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to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be employed to achieve an appropriate trade-off
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, multi-agent systems, and agent based modelling) and energy systems (energy modelling, renewable energy, energy management, and energy in agriculture). The position will be under the direction of Dr. Karl
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
interdisciplinary team at the intersection of artificial intelligence, health, and neuroscience. This position focuses on developing next-generation multimodal foundation models and agentic AI systems that can reason