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relation to road safety for users of motorised mobility devices. The work will take place at NTU (city site), with the research team comprising Prof Duncan Guest, Prof David Crundall and Dr Andrew Mackenzie
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candidate may be employed at Grade E or Grade F depending on qualifications. The project is led by Prof. David Crundall. You will work with a small team to help create and validate our training course, and
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Prof. Rob Morris (Professor of Physics and Maths) at rob.morris@ntu.ac.uk or Dr. Gareth Cave (Principal Lecturer in Chemistry) at gareth.cave@ntu.ac.uk.
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. Supervisor 1: Dr Yasir Ali (Loughborough University) Supervisor 2: Dr Lipika Deka (De Montfort University) Supervisor 3: Prof Marcus Enoch (Loughborough University) Supervisor 4: Ian Murdey (Go Travel
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maintenance, production efficiency, and quality control. While the benefits of ML are significant, its adoption also introduces risks such as data privacy concerns, algorithmic bias, model transparency issues
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to clients, and carers’ scheduling to allocate the time for clients’ visits. Various objectives and requirements of the variety of home-based services have to be taken into account considering carers’ and
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candidate will develop machine learning and algorithmic design skills. The candidate will gain valuable multidisciplinary skills in the area of machine learning and data analytics methods and their
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practices produced with the help of computer algorithms challenge, subvert and threaten the modernist concept of the author. AI generated creative practices have the capacity to seriously disrupt established
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work practices, with 44% of UK workers now in remote or hybrid roles (ONS, 2022), often involving longer hours and irregular schedules (Eurofound, 2017; 2022), making it harder for managers to identify