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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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systems safer, more efficient, and more sustainable. The aim of this project is to design a smart cognitive navigation framework that information from various sensors and learn to make decisions on its own
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within the icing group at Cranfield has captured valuable data on droplet splashing, rebound and secondary impingement through experimental research in the vertical icing wind tunnel at Cranfield
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; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working
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degree or equivalent in a related discipline. This project would suit individuals with academic or industrial experience in electronics, electrical engineering, systems engineering, or AI/data analytics
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Technology Centre (DARTeC), leading advancements in aircraft electrification, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC
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engineering or a relevant area. An MSc degree and/or experience and good knowledge in gas turbine theory, thermodynamics, Machine Learning, and computer programming will be an advantage. Funding Sponsored by
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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significantly reduce the amount of vibration data to be stored on edge devices or sent to the clouds. Hence, this project's results will have a high impact on reducing the hardware installation and operation
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that facilitate seamless integration between AI hardware components and embedded systems, ensuring efficient data flow and processing. Cranfield University offers a distinctive research environment renowned for its