13 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:"-"UCL" PhD positions at University of Plymouth in United Kingdom
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to support early diagnosis and monitoring of conditions such as Alzheimer’s or Parkinson’s disease. The student on this project will gain interdisciplinary training in mathematics, data science, and
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funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description This project develops advanced simultaneous wireless information and power transfer technologies (SWIPT
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Protecting privacy while preventing wandering in people living with mild dementia Director of Studies (DoS): Dr Hai-Van Dang (hai-van.dang@plymouth.ac.uk) 2nd Supervisor: Professor Mona Nasser
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DoS Professor Alison Raby (alison.raby@plymouth.ac.uk ) 2nd Supervisor Dr Martyn Hann (martyn.hann@plymouth.ac.uk ) 3rd Supervisor Dr Matthew Perkins (matthew.j.perkins@plymouth.ac.uk ) 4th
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, or research assistant job) - Solid experience in machine learning and AI (essential) - Experience with imaging data analysis - A collaborative approach to doing science and willingness to help other lab members
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into its latest Ryzen processors, unlocking new possibilities for on-device AI acceleration. This project aims to maximise the potential of AMD’s cutting-edge hardware for healthcare computer vision
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qualification. Background knowledge and experience in engineering and computer science disciplines and in areas such as CFD post-processing (OpenFOAM), wind turbine renewable energy systems, big data management
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energy research, combining laboratory experimentation, computational modelling, and data analysis. Experimental work will be carried out in the world class COAST laboratory, examining floating offshore
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Engineering, Biomedical Engineering, Physics/Medical Physics, Materials Science/Engineering, Chemical Engineering, Data Science/Signal Processing, Biomedical Science, Biological/Human/Life Sciences, etc.) and
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and in-depth information about their vision. This could lead to a paradigm shift for monitoring vision in patients with MS – enabling earlier and more reliable detection of vision-related manifestations