416 data-"https:"-"https:"-"https:"-"https:"-"Newcastle-University" PhD positions in United Kingdom
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The School of Computer Science at the University of Nottingham is pleased to invite applications for a fully funded PhD studentship in deployable, efficient, and trustworthy computer vision. This is
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to augment the funds to cover the extra costs associated with international student fees. Exceptional candidates may be eligible for an International Fee Bursary. High throughput kinetics data for steel
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In this PhD you will help explore a new trajectory for AI research, EVE - everyone virtuoso everyday - to succinctly summarise the drive of the work. That is, we are interested in defining and evaluating a class of AI technology that enable expressive, individual and masterful interactions, like...
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Three 3.5 year PhD studentships in artificial intelligence in medicine or health data science funded by the National Institute for Health Research UCL UCLH Biomedical Research Centre are available
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quantum systems can range from Markovian (“no memory”) to non-Markovian, where information is exchanged in both directions between system and environment. The relationships between light emission, quantum
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. The start date is October 2026. Develop next-generation data storage technologies powered by laser-driven terahertz (THz) fields. Join leading researchers at the University of Manchester to explore
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Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided. Overview Data centres are among
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PhD Studentships in Statistics, Data Science and Machine Learning Award Summary 100% home fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Overview The
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, GNSS positioning is highly susceptible to errors from atmospheric distortions, multipath effects, and receiver noise. Recent advances in deep learning have shown that data-driven pseudorange correction
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of wind tunnel components in elite motorsport. This interdisciplinary project will develop a data-driven approach to understand and predict how process settings, build orientation, machine variability, and