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PhD studentship in Computational Chemistry – Training force fields for computer-aided drug design with machine learning. Award Summary 100% fees covered, and a minimum tax-free annual living
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IAPETUS DLA PhD Studentships – Geography, Natural and Environmental Sciences, Mathematics, Statistics and Physics, Civil Engineering, Computing, & Geoscience Award Summary 100% of tuition fees paid
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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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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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are poised to re-define our future mobility. However, full autonomy is not possible without all-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms
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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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and placement. This research aims to answer the following key questions: - How do varying porosity, core material characteristics, and breakwater geometry influence wave overtopping rates and resulting
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characteristics, and breakwater geometry influence wave overtopping rates and resulting flood extents under different storm surge scenarios, as determined through high-fidelity CFD-DEM simulations? - What is the
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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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). Additional project costs will also be provided. Overview We are seeking a highly motivated PhD candidate with interests and skills in computational modelling and simulations, fluid dynamics, mechanical