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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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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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difficult to deploy outside large data centres. This PhD project focuses on developing resource-efficient computer vision methods that maintain strong performance while dramatically reducing computation
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Programmes: MPhil/PhD English Literature MPhil/PhD English Language MPhil/PhD Modern and Applied Languages MPhil/PhD Creative Writing The School focuses on business information systems, project and operations
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global manufacturers. For details, visit the MTC website . For further information on this PhD position please contact Dr Sara Wang (Sara.Wang@nottingham.ac.uk ) Closing Date: 27th February 2026. Proposed
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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LiDAR and multispectral imageries), and lab analyses. The PhD will benefit from participation in a wider 'large wood' project with over 12-partners (including Environment Agency, SEPA, Natural England
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large herbivores and off-road driving, using the RPI to control for climate-driven variability and incorporating data from allied ground monitoring. This should reveal landscape-scale recovery timeframes
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. This project will use large-scale metagenomic mining to uncover novel phage-host associations and identify phage-encoded enzymes, such as endolysins, with antibacterial activity. By integrating evolutionary
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About the project: Machine Learning to Unlock the Mysteries of Metallic Phase Transitions Supervisor: Dr Livia Pártay, University of Warwick Join a PhD project that goes beyond state-of-the-art to