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simulate hydrodynamic and pollutant transport processes, their computational cost limits their suitability for real-time emergency decision-making. This project addresses this challenge by combining physics
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pressures from climate change, urbanisation and ageing infrastructure. Although high-fidelity numerical models can simulate hydrodynamic and pollutant transport processes, their computational cost limits
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) sensor data. This will be a small system-on-chip designed to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated
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-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms, using signal processing/machine learning techniques, to realise all-weather perception in
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to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated into smaller, faster, more energy efficient and cost-effective hardware
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developing neurotechnologies for treating brain disorders? In this PhD you will work with datasets of neuronal activity in animals and humans. You will apply computational approaches to describe spatial and
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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