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. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD
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and analysis Experience with movement analysis and signal processing (especially as applied to locomotion/ gait) Expertise in developing novel algorithms, but also understanding, optimising and applying
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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learning (ML) for high-fidelity data ‘stitching’. The integration of data from multiple analytical platforms is critical for advancing the understanding of complex biological and chemical systems. This work
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to apply it in selected poor-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging
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are critical especially around congested or critical infrastructures. This research aims to develop decision making and planning algorithms that can mitigate the risks challenging environments of AAM
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to work across disciplines, with an interest (or willingness to develop expertise) in areas such as machine learning, route planning algorithms, aircraft design and testing, and systems engineering. For a
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tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
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communications and sensing. Skills Essential: C1 Excellent programming, algorithm development and scripting skills C2 Research creativity and strong cross-discipline collaborative ability as appropriate C3
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the tool itself and a number of clinical phenotyping algorithms. This new tool will be part of the CogStack ecosystem, currently being deployed to multiple hospitals for near real-time analytics for direct