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Field
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, where opportunities for collaboration and learning abound. About the role The role involves undertaking high quality research as part of an exciting new internationally funded research project
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growing number of PhD students working on the transition to net zero. This project forms part of a collaborative relationship with the Institute of Economics within the Department of Business Science at
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, audio, content), we propose to identify novel ways of mitigating the current and future harms of nefarious AI-generated video. We are seeking to recruit a curious and highly motivated PhD student to work
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Industry Funded PhD Studentship available in the University of Huddersfield’s Biopolymer Research Centre Characterisation and Optimisation of Starch used in Paper Manufacturing Starch plays a
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We are seeking an enthusiastic and capable individual to join our team as a PhD researcher in developing instrumentation and simulations to monitor and track satellites. The successful candidate
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This 4-year PhD programme is fully funded for home students; the successful candidates will receive a tax free stipend based on the UKVI rate (£20,780 for 2025/26) and tuition fees will be paid
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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How to apply: uom.link/pgr-apply-2425 This PhD is fully funded; the successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be
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includes over 500m2 of studio space at UWE’s Frenchay Campus. We invite studentship applications from enthusiastic individuals who are strongly motivated to help push the boundaries of machine learning and