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interpreted by regression and tree-based machine learning algorithms to obtain even better mutants and develop mechanistic hypotheses. Various collaborations with ON-TRACT network partners across Europe allow a
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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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the UK Atomic Energy Authority (UKAEA). The student will be based at the University of Nottingham, but should expect to engage fully with the 3-month full-time training programme in the Fusion Engineering
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unit and then pre-processed data used as the input of the deep learning algorithm. The research will employ the SafeML tool (a novel open-source safety monitoring tool) to measure the statistical
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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predictive performance, computational efficiency, and spatial resolution through algorithm optimisation, tuning, and refined covariates. Assess trade-offs between spatial resolution and other performance
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using cutting-edge computational techniques, including machine learning algorithms. Work collaboratively with an interdisciplinary and international team to refine and validate regional wave and ocean
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of this research programme. The project will be the first of its kind to explore the validity of FIFA-approved skeletal tracking systems for the potential application in on-field gait analysis with the possibility
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to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will develop a novel hierarchical control framework
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project aims to develop state-of-the-art computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the