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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection
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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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that the electrolysers operate safely and reliably while fulfilling the intended specifications. The knowledge gained from the experiments will be used to determine the appropriate risk and reliability analysis
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The project: The deployment of generative AI—particularly Large Language Models (LLMs) based on transformer architectures—in industrial settings poses several critical challenges. Ensuring reliable
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This self-funded PhD research project aims to develop smart sensors based on low-frequency resonance accelerometers for condition monitoring of ultra-speed bearings. The developed smart sensors will
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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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– United Kingdom PhD programme: Harper Adams University PhD programme Fixed term until 30 September 2028 Research project description Agricultural robots and Artificial Intelligence (AI) technologies could soon be
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, and it can have significant effect on train services. The performance encompasses not only of the equipment physical reliability but also includes various factors, such as life cycle, maintainability
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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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