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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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and Britain are world leaders and major exporters. This high technology global industry is worth more than £30 billion per annum. Current challenges are arising from the need to address environmental
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related discipline. This project would suit a candidate with a background in mechanical, control or aerospace engineering, physics, mathematics, or other relevant engineering/science degree. The ideal
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includes funded attendance at elite conferences (e.g., CHES, HOST, COSADE) and specialist training in cryptographic engineering, embedded trust, and side-channel analysis. International mobility is embedded
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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years EligibilityUK, EU, Rest of world Reference numberSATM450 About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university that is a
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
nature makes them susceptible to complex damage modes like delamination, fibre breakage, and matrix cracking, especially under high-velocity impacts from projectiles or debris. Current assessment
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it can also increases the electrical conductivity of composites. As a part of this research project we will develop joint UK projects with aerospace, automotive, marine, and wind turbine manufacturers
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regulations and standards throughout the system's lifecycle. Secure Communication Monitoring: Integrate AI techniques to monitor and enhance the security of communication channels, focusing on detecting and