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. The start date is October 2025. Are you passionate about applying computational science to real-world engineering problems? Do you want to develop digital twins of materials that can predict performance and
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Several types of polymeric materials undergo rapid degradation under both storage and use, unless antioxidants and stabilisers are added to suppress undesirable reactions. This project is co-funded
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environmental impacts of digital activities. You will lead projects modelling the energy usage of different computing equipment (personal computers, servers, High-Performance Computing infrastructure
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alongside New Zealand’s comprehensive landslide inventories to create innovative models of landslide behaviour. The research will combine field work, empirical modelling, and geospatial analysis, ultimately
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of eligible participants, clinical trials in rare diseases often cannot achieve the standard 80% or 90% power requirements, alongside a 5% type I error rate, in the final analysis. There is widespread
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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, where opportunities for collaboration and learning abound. About the role The role involves undertaking high quality research as part of an exciting new internationally funded research project
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possible thereafter. For eligible students the studentship will cover Home tuition fees plus an annual tax-free stipend of at least £20,780 for 4years full-time, or pro rata for part-time study. The student
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and