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, machine learning techniques may be integrated to accelerate simulations and improve medical image processing, ultimately aiding in stroke diagnosis and treatment planning. Please note that this is a self
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trustworthy operation of navigation systems in complex, GNSS-denied scenarios. The ultimate goal is to provide the navigation research community and industry with tools and methods that ensure continuous, high
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AI-electronic systems, ensuring secure communication and operation. Side-Channel Attack Mitigation: Implement techniques to protect systems against side-channel attacks, safeguarding sensitive
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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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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Development courses and unique in the academic sector, industry-scale experimental facilities. The interview process will involve applicants demonstrating alignment of technical competency and motivation
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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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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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