59 parallel-computing-numerical-methods-"Simons-Foundation" positions at Cranfield University
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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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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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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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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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pressure to reduce both energy demand and chemical consumption. Project SandSCAPE, an Ofwat-funded programme, tackles this challenge by integrating purpose-built robots that skim slow sand filter beds while
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the Researchers Core Development programme alongside PhD students, together with access to the University Doctoral Core Research Methods Training (DCRMT) Programme courses, as well as a tailored programme of
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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