47 phd-position-in-data-modeling PhD positions at University of Nottingham in United Kingdom
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The position is open for both UK home and international candidates. PhD Start date: 1 October 2025 Application deadline: 10 June 2025 For further information please email Prof. Michele Degano: michele.degano
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Deployment The PhD programme offers: Training in the theory for solar energy technologies, experimental measurement and evaluation techniques, tools for modelling and predicting PV generation. Opportunities
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EPSRC Centre for Doctoral Training (CDT) PhD in Digital Metal with Rolls-Royce (Enhanced Stipend) Development of Advanced Barrier Coatings for extreme environments Background Applicants are invited
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advantageous. Eligibility and Application The position is open for both UK home and international candidates. PhD Start date: 1 October 2025 Application deadline: 10 June 2025 For further information please
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that present significant problems for data reduction and analysis. This PhD project, in close collaboration with researchers at ISIS Neutron and Muon Source and University of Nottingham, will address this by
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based
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PhD Studentship: Rolls-Royce sponsored PhD scholarship – Intelligent Mechatronics and Robotics Systems Engineering Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing
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We are looking for an enthusiastic PhD student who will undertake original research at Nottingham University Business School. This PhD will contribute to improving the environmental sustainability
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology Applicants are invited to undertake a fully funded three-year PhD programme in partnership with industry
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repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics