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liquid argon. The analysis of the ProtoDUNE data will help to validate calibration techniques and particle identification algorithms. The candidate should have a good knowledge of particle physics and
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also be involved in improving object reconstruction, such as developing advanced algorithms for tau lepton identification or jet substructure / particle-flow techniques to identify Higgs bosons decaying
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, as it involves boiling off lots of water. Innovation is required on multiple scales and there are multiple unanswered questions: Can we replace distillation by other technologies e.g., liquid-liquid
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facial movements. Integrating multiple sensing technologies into a practical and user-friendly wearable headband. Gathering comprehensive datasets from volunteers to simulate various facial activities
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approaches that are able to characterise multiple organs at the same time, as well as the interactions between them. We have developed initial versions of such models and deployed them in small scale studies
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the magnetic fields inside before developing algorithms to accurately reconstruct the field behaviour using long exposures of cosmic rays. Candidates who are interested in multiple projects within our group need
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have designed and introduced new control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the
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massive farming data over long-time scales. These long-term farming data brings more opportunities on leveraging emerging machine learning methods to examine the effects of multiple factors on crop growth