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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
based within the Manufacturing, Materials and Design theme at the Centre for Digital and Design Engineering (CDDE), which offers access to advanced simulation, visualisation, and high-performance
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Students Dr Marco Colombo Application Deadline: 30 December 2025 Details Are you ready to shape the next generation of high-performance engineering systems? Join a cutting-edge, fully-funded PhD project
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Rolls-Royce University Technology Centre (UTC) in manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership
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AI-electronic systems, ensuring secure communication and operation. Side-Channel Attack Mitigation: Implement techniques to protect systems against side-channel attacks, safeguarding sensitive
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that positively develop their workplace relations, environments, cultures, and behaviours. The successful applicant will work with sports coaches recruited from high performance sport, national governing bodies
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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full postgraduate research programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 3.5 years full-time or 7 years part-time. Continuation
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Specified use +4 - covering a full postgraduate research programme Please note that existing postgraduate research students cannot be considered for this funding. Tenable period 4 years full-time or 8 years
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The