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supervisor Dr Lei Xing has built strong track record in circular chemical economy, green energy, carbon capture and utilisation, AI and digitalisation. Supervisors:Dr Lei Xing and Professor Jin Xuan Entry
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background, we welcome applicants from other relevant disciplines, including psychology, sociology, criminology, law, and computer science. This PhD studentship is fully funded for up to 3.5 years with a tax
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contributing to better hazard and risk assessments for decision-makers. This PhD will be part of a broader five-year project funded through the MBIE Endeavor Research Programme, titled, “Hazard, risk and impact
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with Dr Sophie Nightingale (Psychology), Dr George Brown (Linguistics), and Professor Claire Hardaker (Linguistics) to add to the evidence base needed to design and develop approaches to mitigate
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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
Christina Latsou 2nd Supervisors: Professor John Erkoyuncu , Dr Bernadin Namoano Entry requirements Applicants should hold a First or Upper Second Class UK Honours degree (or international equivalent) in a
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(including 7 full professors) and approximately 120 PhD students and post-doctoral research fellows. The group has excellent facilities for experimental work including approximately 2500m2 of research space
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Lead Supervisor name: Professor Katherine Appleton, email: k.appleton@bournemouth.ac.uk Project description Aims: This project aims to use a systematic approach to design, develop and test novel
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150 members, with 18 academics (including 7 full professors) and approximately 120 PhD students and post-doctoral research fellows. The group has excellent facilities for experimental work including
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for candidates with a background in meteorology, climatology, physics, engineering and any related discipline, and a strong interest in applying advanced physical and computational methods to real-world