46 postdoctoral-image-processing-in-computer-science PhD positions at University of Nottingham
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through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing
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of Medicine) – neil.nixon@nottingham.ac.uk Funded by the Mental Health Mission, Office for Life Sciences/NIHR, as a single PhD Studentship Award, we have a fully funded (stipend at UKRI rates, PhD fees (for 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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engineering. Expertise in numerical tools (Ansys, JMAG, .etc) and programming are desirable. Experience in electrical machine prototype development would be advantageous. Eligibility and Application
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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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combination of overseas field work (Europe and other locations), image based and laboratory work to characterise soil properties to address the questions above. The imaging work will be a combination of GIS
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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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(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be