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technologies are increasingly used to support animal health and welfare, yet their success depends on how farmers, animals, and systems interact. This PhD will explore the use of the Epiherd digital platform
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high-resolution climate data, fault records and network models, the project will quantify how hazard conditions interact with asset characteristics and network structure to produce service losses
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feasibility on a system level, this project aims to develop approaches that offer handles to interaction designers in reinventing their practices for a less resource intensive future that is resilient
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Doctoral Training Grant Funding Information This funding model includes a 42-month funded PhD Studentship, set in-line with UK Research & Innovation values. For 2025/6, this will be £20,780 per year
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will work directly with Prof. Aurélie Perrier, specialist in computational photochemistry, and will interact closely with all members of the SIMULACTOR consortium. The quantum chemistry codes required
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-EM structures to rationally design new peptide mimetics targeting the relevant interaction sites. This work will be performed in close collaboration with several other groups in the LipAgg network
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-of-the-art in multi-agentic AI, and how to interact with external models and tools. Design, develop, and evaluate multi-agentic AI model architectures to gain and improve our insights in agriculture from
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resilient. The PhD student will undertake a full research programme: interviewing participants, leading focus groups, designing studies, analysing data, developing models, designing technological, educational
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computer interaction in this context). This work will contribute to the empirical co‑design and testing of principles guiding the development and deployment of AI systems for assisting judicial decision
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used to support animal health and welfare, yet their success depends on how farmers, animals, and systems interact. This PhD will explore the use of the Epiherd digital platform through a One Welfare and