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Cardiomyocyte Dynamic Network Analysis with Machine Learning (Ecidna-ML) This project represents a new approach to map dynamical interactions in networks of human cardiac cells. Network dyssynchronisation is a
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: Forecasting Future Environmental Impacts of Photovoltaic (PV) Manufacture Using Machine Learning Techniques This PhD will suit applicants who are keen to make a difference in how we utilise advanced materials
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the development of machine learning, data-driven method has become a powerful tool for civil engineers. Especially, Physics Informed Machine Learning (PIMM) can be used as a comprehensive analysis considering both
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and progamming skills; Knowledge of Python.; Knowledge of Bayesian statistics, machine learning, and optimisation, or a willingness to learn. This scholarship is open to candidates of any nationality
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and provide a second opinion with a level of certainty to assist human experts. From the aspect of research methodology, the research work involves image processing, data analytics and machine learning
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electronics and machine learning. Proficiency in programming languages such as Python, C/C++ and MATLAB. Demonstrated relevant project experience. Excellent analytical and problem-solving skills. Due to funding
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interdisciplinary researchers to grow ideas from concept through to manufacture, instrumentation, and testing, alongside advanced computational mechanics, machine learning, and data analytics workflows. For more
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with the latest research and developments. Working closely with the project partner QinetiQ, this project will combine state-of-the-art machine learning methods, natural language models and image
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computational mechanics, machine learning, and data analytics workflows. For more information on the facilities, a virtual tour is available. The dynamic group (>20 PGR students and Research Staff) leverages
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are sensitive to defects, which can lead to production issues and high costs. The project will develop methods to inspect wafers more effectively, using machine learning to identify critical defects in the latest