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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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technologies. Metamaterials, engineered to exhibit properties not found in naturally occurring materials, offer an innovative pathway to overcome these limitations. By designing intricate periodic or quasi
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performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
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Cranfield University invites applications for a PhD funded by Thames Water through the Ofwat Innovation Fund. The studentship covers full Home tuition fees plus a tax free stipend of £24,000 per
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
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Embark on a thrilling, fully funded four-year PhD journey, with an enhanced stipend of £25,726 per year, and deliver new evidence on how nature-based solutions can reduce the occurrence and mitigate
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. This PhD will be supervised by Dr Enric Grustan (Lecturer, Cranfield University) and Dr Adam Baker (Visiting Fellow at Cranfield and Senior Project Engineer, Magdrive) At a glance Application deadline30 Jul
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This PhD opportunity at Cranfield University invites ambitious candidates to explore the frontier of energy-efficient intelligent systems by embedding AI into low-power, long-life hardware platforms
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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
at scale? Digital twins offer a promising foundation, but to truly support engineering decisions, they need to go beyond simulation and begin to interpret and reason about the systems they represent