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Engineering, Faculty of Engineering and Applied Sciences, Cranfield University, in the area of performance simulation, analysis, and optimization of supercritical CO2 power generation systems. Cranfield has
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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advanced technology and business needs, creating smart monitoring systems, predictive maintenance solutions, and digital twins that solve pressing challenges across healthcare, energy, aviation, and
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to discover the fundamental mechanisms responsible for damage and deformation. About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university
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integrating advanced vision and language transformers with an Explainable AI (XAI) layer, the project aims to create a robust system for accurate threat identification, providing actionable intelligence
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-assurance positioning in safety-critical applications. Cranfield is a specialist postgraduate university that is a global leader for education and transformational research in technology, management, defence
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This project is sponsored by EPSRC, Cranfield University and a consortium led by ETN global. ESPRC will provide stipend (£22,000 per annum) and cover UK fees. The consortium will provide supervision
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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technology, management, defence and security. Cranfield is recognised for delivering outstanding research addressing contemporary global challenges with economic, environmental, and social impact for business
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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