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programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking
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carried out at Cranfield in the continuity of what is done by considering the new experimental developments. For these CFD studies, numerical tools and super computers at Cranfield and Loughborough will be
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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validation experiments for modelling • Computational fluid dynamics techniques • Finite element analysis method • Reviewing literature, planning and managing research, writing technical report / paper
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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multilayer printed circuit boards (PCBs). It draws from disciplines including electrical and electronic engineering, embedded systems, computer vision, and cybersecurity. The ability to verify hardware without
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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information from unintended data leakage. Communication Resilience Against Jamming and Spoofing: Develop AI-driven methods to detect and mitigate jamming and spoofing attacks, enhancing the robustness
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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. These insights will directly inform future nature-positive urban design. If you are passionate about ecological systems, urban sustainability or applying advanced quantitative methods to real-world environmental