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Field
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engineering, operations research, supply chain management, or a related field. Experience with system modeling or scenario analysis (e.g., system dynamics, agent-based modeling, MCDA, causal mapping
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agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware spectroscopy workflows. The researcher will work closely with a multidisciplinary team of X-ray physicists and
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Philanthropy and is fixed-term until 31 Dec 2027. A further extension to this would be based on funding availability. You will conduct hands-on empirical research in multi-agent security and agentic AI security
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optimization and LLM alignment: design preference-based training and fine-tuning methods (RLHF, PPO, DPO, reward modeling) for medical and multilingual LLMs. Agentic and tool-augmented AI systems: develop
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up results clearly, and manage associated administrative duties effectively. Your expertise will include computational modelling of agent behaviour, practical development of agent models using symbolic
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tailored to radiology workflows. Developing software tools that supports reliable model comparison, ablations, and useful documentation (for human users and agentic use). Communicating results effectively
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, or trustworthy AI agentic AI, multiagent systems, sequential decision making, and LLM-based reasoning embodied or physical AI, robotics, autonomous systems, or intelligent infrastructure systems strong programming
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that are researched by PhDs and Postdocs to develop HI. It is our aim to be able to use the developed metrics and methods to evaluate how well these projects provide solutions for HI as well as establish synergies
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Division of Time 80% Research: Build, train, and evaluate cutting-edge AI models and multi-agent systems for conservation genomics; perform feature engineering using chromosome-level genome assemblies. 15
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the following: digital twins, cyberphysical systems, human-centred AI causal modelling, uncertainty quantification, explainable AI, or trustworthy AI agentic AI, multiagent systems, sequential decision