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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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degree which includes a substantial research element, with a score of 65% or above in the taught modules and 65% or above in the dissertation. Complete the PhD Programme online application . Your
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
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nationals only) and research costs) three-year full-time PhD available to start on the 1st October 2025. The overall theme of this PhD programme is improving clinical assessment and research access
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which