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Title: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science Research theme: "Materials Characterisation" "Data Science and Machine Learning in
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data sources to answer important population-level questions that will inform health technology assessment, policy, and practice. The successful PhD student will be embedded within an interdisciplinary
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Characterisation" "Data Science and Machine Learning in Materials" "Plastics Recycling and Circular Economy" How to apply: https://uom.link/pgr-apply-2425 How many positions: 1 This 3.5 year PhD is open to UK
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quantum chemistry (QM), machine learning (ML), and high-throughput experimentation (HTE). The objective is to develop a data-driven framework that enhances the efficiency and effectiveness of catalyst
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) 4th Supervisor: Prof. Phillip Buckhurst, (phillip.buckhurst@plymouth.ac.uk ) Applications are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2025
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bioprocessing technologies to deliver efficient pathways for upcycling captured carbon into high value products. The successful candidate will have a PhD, or be studying towards a PhD, in synthetic biology or a
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assessment and quantification of risk and an understanding of Risk Behaviour; Information Systems; Management Science and Operations Management. For subject-specific queries, please contact Dr Sasan Barak
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PhD Studentship: Revolutionising Litz Wire Development for Next Generation Ultra-High Speed Propulsion Motors The Manufacturing Technology Centre UK, and University of Nottingham This project offers
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PhD Studentship: Carbon Nanotube (CNT) Winding Development for Electric Motors The Manufacturing Technology Centre UK, and University of Nottingham This project offers an exciting opportunity
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tunnel (IWT) based at Cranfield which has a strong collaborative history with industry in the field of atmospheric icing science research. This programme provides the PhD candidate with an outstanding