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This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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experts in the prognostics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University. About the host University/Centre Cranfield is an
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part of an annual cohort, you’ll benefit from world-class training facilities across various universities and industrial settings, engaging with experts and stakeholders from diverse backgrounds. Based
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
Fully funded PhD at Cranfield University, supported by the EPSRC DTP and Rolls-Royce. This 3-year project covers tuition fees, a tax-free stipend, and funding for training, conferences, and a
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inclusion of student-led activities. You will be part of an annual cohort and will receive training at different universities and industrial partners providing world-class facilities in a supportive
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. You will be part of an annual cohort and will receive training at different universities and industrial partners providing world-class facilities in a supportive, innovative, inclusive and interactive
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University. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power Engineering, Cranfield University, in the area of gas turbine performance, diagnostics and prognostics