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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By establishing an understanding of "what normal looks like", these models will detect deviations from the norm and
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to analyse cardiovascular images, primarily focusing on MRI. In your research you will train models to learn a distribution of normal cardiac anatomy and function (including motion) from healthy subjects. By
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computational tools to support the safe and ethical deployment of AI in clinical settings. The research focus is on AI performance monitoring, distribution shift detection, bias assessment, and stress testing
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January 2026. Later dates are possible, please contact Dr Andrew Viquerat once the deadline passes. You will need to meet the minimum entry requirements for our PhD programme . How to apply Applications
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focus on solid dosage forms and 3D printed drug products. The research will integrate advanced imaging, computational modelling, and pharmaceutical sciences to improve the resolution, reproducibility, and
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, please contact Dr Isabella Guido once deadline passes. You will need to meet the minimum entry requirements for our PhD programme . We are seeking a highly motivated and skilled candidate with a
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experimentation and finite-element modelling. Research themes would be flexible including green steel formability under the EPSRC ADAP‑EAF programme for automotive and packaging applications; or micromechanical
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% of their time on teaching/related professional development. Teaching duties will be agreed annually with Programme Directors and tailored to the demonstrator’s expertise and career goals. Applicants will be
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians