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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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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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-generation intelligent hardware. As embedded AI hardware continues to redefine intelligent computing, this PhD offers direct access to cutting-edge silicon design workflows through Cranfield’s EUROPRACTICE
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This fully funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA) and RES Group, offers a bursary of £25,000 per annum, covering full tuition fees. The project focuses
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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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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems
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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 self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM