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of your current level of study, academic background, any relevant experience and your motivation to study this PhD project. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a
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, which is not possible with current systems. It aligns with key STEM themes and EPSRC’s strategic focus on ‘Engineering’, ‘Health and Medical Technologies’, and ‘AI, Digital, and Smart Applications
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The project: As wearable technology becomes increasingly ubiquitous in our lives, it is urgent we better understand how we might use the technology and how the technology can enhance our lives
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
) in a relevant discipline such as aerospace engineering, mechanical engineering, electrical engineering, computer science, applied mathematics, or a closely related field. Experience or interest in
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of the assembly of these complex microbial communities using ecological theory and mathematical models. The questions we address are: (1) how does the microbial community change during cultivation
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research opportunity focuses on advancing large-scale additive manufacturing using metal wire as feedstock and electric arc as the heat source. The project aims to develop an innovative and efficient method
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, the College of Technology and Environment , and the College of Society and Professions . These opportunities are ideal for highly motivated individuals with a strong academic background and a keen interest in
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electrical/mechanical engineering. Expertise in numerical electrical machine design tools (Ansys, JMAG, .etc) as well as corresponding scripting skills are desirable. Experience in electrical machine prototype
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a thorough knowledge of mechatronics engineering for electric vehicle systems and to have a working knowledge of a range of topics within the sphere of their chosen discipline. They will also be
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2025. Encouraged by the continuing success of modern machine learning (ML) techniques, researchers have become ambitious to develop ML solutions for challenging science and engineering problems with