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Department: Materials Title: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science Application deadline: 15/09/2025 Research theme: "Materials
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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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by the Ada Lovelace Centre and the University of Birmingham. This interdisciplinary project is ideal for candidates with a background in physics, materials science, chemistry, or computational science
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or strong Upper Second-Class degree in Mechanical Engineering, Materials Science, Physics, or a related discipline. A background in computational mechanics, materials modelling, or engineering
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
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: Flexible, likely start February 2026, for 42 months. Candidates must possess or expect to obtain, a 2:1 or first-class degree in Engineering, Chemistry, or related physical sciences related discipline. To
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possess or expect to obtain, a 2:1 or first-class degree in Engineering, Chemistry, or related physical sciences related discipline. To apply: send covering letter, CV and academic transcripts by email to
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Institute of Photonic Technologies to be undertaken within the College of Engineering and Physical Sciences at Aston University. Financial Support This studentship includes a bursary to cover the fees rate