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. Analysis of images will investigate the efficacy of manual digital approaches (e.g., Dot Dot Goose) and the development of a marine litter characterisation and quantification algorithm for automated analysis
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Primary Supervisor -Prof Michal Mackiewicz Scientific background Marine litter is a key threat to the oceans health and the livelihoods. Hence, new scalable automated methods to collect and analyse
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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algorithms for data processing, assisted or automated flaw detection, 3D EM solvers, and synthetic aperture radar (SAR) focusing will be used to refine spatial resolution. Applicants should have, or expect
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brain decoding methods and test the extent to which these generalise across brain areas and species. You will be working with an interdisciplinary team led by Prof Andrew Jackson funded by the Advanced
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
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physics all the way to numerical simulation algorithms? Then apply now to join our team of researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere