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equipment, and have access to valuable industry data. The student will benefit from opportunities to present at leading international conferences. Additional training in software-defined radio, hardware-in
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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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 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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mitigating jamming and spoofing threats in real-time. Integration of Trusted Execution Environments (TEEs): Investigate the use of TEEs to create secure zones within embedded systems, facilitating secure data
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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
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. Despite some success stories of the use of ultrasound/AE-based technologies for CM of low-speed bearings, high investment cost for hardware and software is the main bottleneck in adopting these technologies
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equipment, and have access to valuable industry data. The student will benefit from opportunities to present at leading international conferences. Additional training in software-defined radio, hardware-in