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Field
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, and Internet-of-Things / Industry 4.0 technologies. Knowledge of computer science principles and modern AI approaches in computer vision and/or time series analysis is a plus. The position requires
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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
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
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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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Engineering (full time)' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: a ‘Personal Statement’ (this is a mandatory field) – Use this
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benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions
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Award Summary This is a 4-year studentship. Stipend of £18,873 (stipend may be uplifted subject to confirmation) and home fees are covered. Overview Interested in using your computational and
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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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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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may be possible, please contact Dr Mark Whiting once deadline passes. You will need to meet the minimum entry requirements for our Engineering Materials PhD programme. Candidates must meet Surrey