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Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme. Cranfield Doctoral Network Research
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) in quantitative biology, statistics, or a related discipline, and have experience using statistical modelling and data analysis to address predictive or inferential questions in ecological
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vessel, the fully turbulent flow channel, the towing tank and the combined wind, wave and current tank. For more information about the School of Engineering and our research, please click here . See our
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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-class/high 2:1 degree in civil or geotechnical engineering. A relevant master’s degree and/or employment experience will be an advantage. English language requirements: Applicants must meet the minimum
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding
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the recording of substrate-borne vibrations produced by earthworms (and other invertebrates) in situ. To fully exploit this emerging technology there is a need to unravel the meaning within the data. As such
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stresses. Based on the experimental data, a semi-empirical model to be developed to assess insulation degradation and identify failure signatures that can inform future predictive asset management strategies
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stipend at the UKRI rate (£20,780 in 2025-26 for full time students), and a contribution towards research and training costs; A personalised training programme, to develop research, communication
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of Edinburgh and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National