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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based on the use of state-of-the-art
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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Motivation: Soft and flexible materials (e.g. polymers, hydrogels) have revolutionised many areas of science and technology ranging from flexible electronics to soft robotics. Scientists now predict
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
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Fees for 4 years (Full time), £12,000 stipend for 3 years We are pleased to invite applications for a funded PhD studentship exploring how a curated Arts Public Programme can address pressing issues
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or international equivalent in a subject relevant to the proposed PhD project (electrical engineering, electronics engineering or computer engineering). Enthusiasm for research, the ability to think and work
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should have or expect to achieve, at least a 2:1 (or equivalent) in any engineering degree programme, physics or mathematics. English language requirements: Applicants must meet the minimum
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with: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed