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and life-cycle assessment will broaden your professional network while a dedicated training budget allows you to attend specialised courses—such as drone photogrammetry or advanced bioinformatics—and to
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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testing) to understand and tailor the physical and chemical interactions within these complex structures. Cranfield University is internationally renowned for its research into materials for extreme
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professional network spanning academia, industry, and national research centres. Through this multidisciplinary project, the student will develop expertise in: Contribute to the development and operation of
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to design and prototype a ground-based automated inspection system capable of detecting complex damage types in composite aircraft structures, such as delamination and lightning strike damage. Leveraging
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deployment of IoT-enabled sanitation systems worldwide, there is a critical need for intelligent software platforms that can bridge the gap between complex technical systems and end-users while providing
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in avionics, electrification, industrial automation, and healthcare. However, traditional electronics struggle with AI’s growing computational complexity, lacking real-time adaptability, energy
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will publish high-quality research papers and present their work at international conferences to build global networks with leaders in academia and industry. We invite students interested in joining
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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knowledge co-evolution and addressing complex challenges in a super-intelligent society. This project is situated within the rapidly evolving field of Cyber-Physical-Social Systems (CPSS), which is of