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for Security Operations Centres (SOCs) while pioneering strategies for quantum-era resilience. This project sits at the intersection of Artificial Intelligence, Cybersecurity, and Explainable Computing. It
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) offering a secure start to the work. This PhD will be an inter-disciplinary, using expertise on meteorology and co-occurring hydro-meteorological hazards (Chen, Hillier, Bloomfield) and insurance industry
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opportunities for professional and personal development through established collaborations such as the Applied Research Collaboration (ARC) and NIHR Patient Safety Research Collaboration (PSRC). The studentship
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(to make the egg-carrying embryo-sac). Both are essential to seed production, and so our food security. Many of the genes that control male meiosis are known[1] but female meiosis is very different and
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computational fluid dynamics and numerical modelling will be used to simulate performance under varying runoff scenarios, pollution loads and climate conditions. By developing advanced road gully designs with
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and signal processing methods using machine learning techniques to enhance the resilience, efficiency, and security of cell-free massive MIMO systems, which are expected to play a key role in next
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an implementation support package Project Supervisors: Dr Sam McLean Prof Beth Fylan Dr Justine Tomlinson Jaspreet Sohal Project Description: This is a fully funded training programme to conduct research
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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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Loughborough serve as contrasting case studies, pairing a metropolitan centre with a smaller town to secure transferable findings. The project provides advanced training in spatial analysis, AI methods, and
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sponsored by the MTC, any successful candidate would need to pass their security checks prior to the commencement of the PhD. Motivation This project will develop an innovative co-axial water-mist-assisted