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curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model experimentation and training. Science of Deep Learning: Exploring mechanistic
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
that are contextualized and intrinsically safe. Most work on VLM/LLMs for robotics focused on generating sequences of actions and plans from high level goals, offline, only targeting autonomous robots isolated from humans
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- and LLM-enabled methods and tools to structure, harmonise, and analyse clinical data in a FAIR, privacy-preserving, and clinically meaningful manner, with particular attention to unstructured and
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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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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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and decision support (e.g., LLMs, retrieval-augmented generation, agentic systems) Building production-quality prototypes suitable for pilot deployment in judicial settings, including robust retrieval
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language model (LLM) methods to unlock information from Dutch electronic health record (EHR) free text for secondary use in research. Electronic health records contain a wealth of relevant patient
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the future of programming education at AAU. By working within live teaching environments, the candidate will gain firsthand experience with pedagogically driven AI innovation, local LLM infrastructure
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pipelines by combining statistical, synthetic, and decentralized methods to improve both the privacy and utility of anonymized datasets. Moreover, this research will examine the potential of AI and LLM
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, longitudinal patient and population registries and biobanks. Project description Large language models (LLMs) enable the extraction of clinical information from unstructured medical text. However, current LLM