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applicants embarking on a brand-new LSBU research programme—current PhD students and LSBU staff members are not eligible for this award. Why choose LSBU for your doctoral journey? LSBU is a dynamic, applied
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PhD project (such as Electrical Engineering or Computer Science) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work
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departments and research centres in the School of Policy and Global Affairs, offering potential for interdisciplinary research in politics, sociology, or criminology. About the programme Upon joining our PhD
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Application deadline: All year round Research theme: Systems and Control How to apply: uom.link/pgr-apply-2425 This 3.5 year PhD project is funded by The School of Engineering and is available to home students. The successful candidate will receive a tax free stipend set at the UKRI rate...
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up to £24,237 per year on successful progression to PhD at the end of the first year of the programme for students undertaking industry-funded PhD projects. We are recruiting high-calibre students
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Background Network Rail operates several telecom networks which provide connectivity for various signalling systems. Therefore, the performance of telecoms assets is integral to how the railway system operates
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of developing a computational model to simulate hydro-sedimentary dynamics and morphology between restored patches to explore conditions favourable for restoration. Validated with data on vegetation cover and
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based in School of Computing and Creative Technologies at The University of the West of England , Bristol where they will join the Music Interaction and Computational Arts (MICA) Lab . The MICA Lab is
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mixed reality Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780 per year for 3.5 years. Lead Supervisor’s full name
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging