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Field
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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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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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different types of data—such as audio, motion, images and sensor signals—can be combined using minimal representations without relying on large, computationally intensive models. Key objectives include
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-on experiments & development and opportunities for travel to international facilities. This project is supported by the large investment of a URKI Future Leaders Fellowship to identify, synthesise and explore new
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and Innovation rates Payment of university tuition fees The budget for project costs is £9,000 which can be used for computer, lab, and fieldwork costs necessary for you to conduct your research
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social engagement. Studying its link to cognitive function and dementia risk provides a unique opportunity to understand how large-scale social policies shape healthy ageing and to generate evidence to
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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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on combining innovative technologies such as remote monitoring, large language models, machine learning, blockchain, and eco-accounting to enhance the efficiency, security, and sustainability of e-bike charging
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: (1) Astronomical spectroscopy, preferably exoplanet spectroscopy using HST, JWST, large ground-based telescopes and/or other facilities at low or high resolution, including data reduction and time
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social engagement. Studying its link to cognitive function and dementia risk provides a unique opportunity to understand how large-scale social policies shape healthy ageing and to generate evidence to