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Determining the Oxidation Creep Interaction in Uncoated and Coated Steels using a Novel Torque-Load Test Method This exciting opportunity is based within the EPSRC's Centre for Doctoral Training in
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Course: PhD studentship Project title: Exploring a One Welfare approach to human-animal-computer interaction in digital dairy technologies Principal supervisor: Charlotte Doidge Other supervisors
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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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human-animal-computer interaction lens, examining how digital tools shape farmer-cow relationships, perceptions of care, and welfare‑related decisions. The project will investigate how farmers engage with
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accountability, transparency, and oversight. This project addresses these challenges by combining experimental human factors methods with interdisciplinary perspectives on law, governance, and technology. The work
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working hands-on with a wide range of individuals. Equally, they should be comfortable with statistical analysis of data. The research will focus on creating consumer-centred testing methods, exploring how
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working hands-on with a wide range of individuals. Equally, they should be comfortable with statistical analysis of data. The research will focus on creating consumer-centred testing methods, exploring how
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working on this problem for several years and have developed methods that shape the incoming light with the equal but opposite distortion to that imposed by the sample to produce a high-quality image deep
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addresses two intertwined goals: Improving Human Training: Developing adaptive haptic training strategies that help operators refine their skills through real-time skill estimation, multimodal feedback, and