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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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, 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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LLM Agents: Foundations, Attacks, and Defenses”. Your work assignments Large language model (LLM) agents represent the next generation of artificial intelligence (AI) sys- tems, integrating LLMs with
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area of AI security, on the topic of “Memory Poisoning in LLM Agents: Foundations, Attacks, and Defenses”. Your work assignments Large language model (LLM) agents represent the next generation of
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, especially large language models (LLMs), enable the development of interactive AI agents that can support human learning in complex, safety-critical environments. Human-centered AI in this project means
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verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based automated reasoning tools such as ESBMC (https://github.com/esbmc/esbmc ) to address safety and reliability
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The Bernhard Nocht Institute for Tropical Medicine (http://www.bnitm.de/en ) is the largest Research Institute for Tropical Medicine in Germany and is the National Reference Centre for Tropical
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currently in a unique position of benefiting from the hindsight of billions of dollars spent in research and development in large-language models (LLMs). This second-mover advantage position creates
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the field of frugal or green AI TECHNICAL SPHERE You have a proven experience in frugal, green or low-resource AI Strong grasp of deep learning architectures (CNN, RNN, Transformers, LLMs). Experience in fine
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related to staff position within a Research Infrastructure? No Offer Description Your tasks: Development of methods for designing embedded systems based on large language models (LLMs) Investigation