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statistical modelling, epidemiology, population data science and health technology assessment, with the opportunity for their research to directly inform healthcare policy and practice. The successful student
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an appropriate field of Engineering. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered. Subject Area Artificial Intelligence, Computer Vision
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This research opportunity aims to hire PhD students as a self-funded program. By analysing retinal images with deep learning technology, early detection of Alzheimer’s disease may be possible. By
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Use of surface textures to improve tactile perception Department of Mechanical Engineering PhD Research Project Self Funded Prof M Carre Application Deadline: Applications accepted all year round
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the utilisation of the large data volumes captured of torso surfaces to better translate knowledge to support garments. The studentship will appeal to students with a sports engineering/technology or other relevant
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Development (CPD), which is embedded throughout your 4-year research scholarship. Eligibility requirements Candidates with a Meng/MSc in Civil Engineering, Mechanical Engineering, Applied Mathematics or Applied
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, sports engineering/technology or biological engineering background. It is intended that a variety of qualitative and quantitative data collection techniques will need to be used. There is also scope to use
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tools. Entry requirements Applications are invited from individuals with a first or upper second-class degree (or equivalent) in a relevant discipline such as, engineering, maths, computer science, etc. A
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Applications are invited for a PhD studentship in the Department of Engineering. The successful candidate will have the opportunity to work on an investigation into tunnelling-induced ground
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Post Title: Research Fellow in structural health monitoring of composites using optical fibre SBU/Department: School of Physics, Engineering and Computer Science FTE: 1.0FTE (Working 37 hours per