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arrhythmias, and 900,000 with heart failure. Medical imaging techniques, such as CT, MRI, and X-ray, are vital for diagnosing and guiding the treatment of cardiovascular diseases. This project aims to develop a
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, using signal processing/machine learning techniques, to realise all-weather perception in autonomous vehicles with high-quality multiple-input-multiple-output (MIMO) radar sensing/imaging. The project
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Applications accepted up till Monday 15th December, 2025. Competition funded PhD Project. Supervisors: Dr Yi Feng (The University of Edinburgh), Dr Mattias Malaguti (The University of Edinburgh
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in
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processing techniques that take full advantage of these capabilities, in order to translate them into optimal radar performance. The purpose of the PhD is to lay down theoretical and practical foundations
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assess how effectively imaging techniques capture or enhance the taxonomic resolution of traditional net sampling. Training You will gain skills in plankton taxonomy, image processing, ecological
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Amount: Annual stipend for 3.5 years at UKRI stipend rates (set at £20,789 in the AY 2025-26), plus tuition fees waived. Level: Postgraduate research (Edinburgh campus; full-time) Eligibility: UK
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on biological tissues and medical image processing. The studentship includes many opportunities for the candidate to build their professional network by presenting their work at conferences and discussing
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have the opportunity to develop their computational modelling capabilities in this project, alongside learning new skills such as testing on biological tissues and medical image processing
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techniques for modelling and monitoring the infusion and curing process and this PhD will bring these elements together to form a digital twin of the process. This digital twin will be used to predict