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with transferable expertise applicable across AI-driven domains. Application Process To apply, please send a CV, cover letter, and transcripts to Dr Christopher Wood (christopher.wood@nottingham.ac.uk
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. Application Process To apply, please send a CV, cover letter, and transcripts to Dr Christopher Wood (christopher.wood@nottingham.ac.uk ) and Dr Grazziela Figueredo (g.figueredo@nottingham.ac.uk ). Informal
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overseas equivalent) Nationality restrictions This funding is available to all nationalities. Application procedure You must submit your completed online programme application for a place on your chosen PhD
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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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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
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explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers the opportunity for the PhD student to lead the development of innovative simulation tools
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supercritical water systems to generate samples that will help optimise a process that will then be scaled into pilot and large scale pilot systems with partners in the consortium. Aim This project will focus
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drive the gradual development of these technologies toward real-world applications. This involves engineering experimental hardware for cell culturing workflows, optimizing experimental processes, and
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programme. Successful candidates are expected to participate fully in the academic life of the University. Remote-only arrangements will not be considered. Application Process To apply, please send
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. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter-personal communications skills. Desirable skills: Previous experience in medical