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benefit from world-leading infrastructure uniquely suited to support the programme, i.e. a fully operational network of Commercial-off-the-Shelf (COTS) primary air surveillance radars specially modified
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or machine learning. Excellent programming skills (e.g., MATLAB, Python, or ROS), a strong publication record, and an ability to work collaboratively in multidisciplinary environments are essential. Prior
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academic performance in undergraduate and, where applicable, Master’s coursework Advanced programming skills in R and Python Familiarity with econometric techniques, especially panel data methods Ability
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benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions
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achievement. The SUIPRES Scholarship covers the difference between the International and the Home tuition fee for the duration of the PhD/Professional Doctorate programme. Successful candidates will be charged
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through health, retail, mobility, energy and communications. This exciting PhD programme will first use qualitative methods to investigate how the public access and use OTC medications for a range of common
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methods experience. Quantitative applicants are expected to have worked with large datasets or equivalent project experiences, and have programming skills such as R coding (preferable) and communication
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bioinformatic tools and focused on clear interpretation and communication of this data. This project is part of an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in
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an exciting new Doctoral Training Programme in Microbial Genomics for Health Protection in collaboration with the UK Health Security Agency (UKHSA). This is funded by NIHR as part of a Health Protection Unit in
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research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as