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that can be run. Emulating expensive processes could allow more data to be generated from better models, at lower cost. The central science question is: how can machine learning and evolutionary computation
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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for rare or threatened animals (the “long-tail” problem). Moreover, current models give little indication of when they might be wrong, restricting their use in conservation. This PhD will tackle both issues
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is appropriately multi-disciplinary, at the interface between AI, environmental science, meteorology and epidemiology. Corresponding skills (machine learning, environmental and public health data