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the Photonic Quantum Information group (PQI) led by Professor Ian Walmsley in the area of quantum machine learning. You will engage in advanced study and academic research, working to develop and carry out
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, machine learning, multiscale and multiphysics simulation, computational anatomy, medical image analysis, and integration of wearables and biosignal processing, applied to conditions ranging from cardiac
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multiple symbolic fields, including official political discourse, academic debates and selected cultural outputs. Methodologically, it adopts a mixed-methods approach, combining machine-learning–enhanced
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large
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language processing, machine learning and skills taxonomies, you will help generate meaningful insights into current and future engineering skills needs. Your work will support industry, policymakers, educators and
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publishing work as lead author. Experience with machine learning methods for modelling human learning, such as knowledge tracing and/or experience with conducting research that involves prompting or fine
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) in Physics or a related field. Previous experience in cosmological simulations, analysis of cosmic microwave background and/or large-scale structure datasets, machine learning methods applied
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thrusts within the lab’s multi-agent security programme. You should possess a completed PhD/DPhil (or thesis submitted by the start date) in Computer Science, Machine Learning, AI, Security, Robotics
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the role The PDRA will carry out research on probabilistic circuits (PCs) and tree-based machine learning methods for generative modelling, with a particular focus on responsible AI. The project builds
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interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Christopher Summerfield. The post-holder will have responsibility