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into hydrogen and nitrogen under practical onboard conditions. Successful candidate will develop and apply computational methods, such as density functional theory based atomistic modelling and machine learning
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About the Role A fantastic opportunity has arisen for a Senior Research Fellow to join the Power Electronics, Machines and Drives Research Institute (PEMC) at the University of Nottingham and become
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machining (milling and/or turning) you will contribute to the design and manufacture of high-quality parts that support the world changing research and teaching ambitions of the University. You will
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This is an exciting opportunity for an ambitious and talented researcher to join the Power Electronics, Machines and Control (PEMC) Research Institute at the University of Nottingham and become a
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research in areas including Artificial Intelligence, Big Data and Visual Analytics, Computational Intelligence, Machine Learning, Software Implementation and Testing, and their applications in manufacturing
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the university, genomic and metabolomic measures, offering novel potential to explore the physiological basis for imaging measures and apply machine learning in a radiological context. You will join an established
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and machine learning, uncertainty quantification, Bayesian non-parametrics, image analysis, geometric statistics, and stochastic processes with an internationally leading research group in epidemic
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Sciences), and Markus Kaiser (Medicine). We draw on and develop a wide range of computational approaches to data, including unsupervised machine learning, network theory, and dynamical systems theory. What
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engineering disciplines. There will be opportunities for you over the apprenticeship period to learn and train on a wide range of cutting-edge engineering technologies and disciplines including: CNC machining
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(Sommerschield et al. 2023 ‘Machine Learning for ancient languages: A survey’, Computational Linguistics, 49.3) mean that it is time to test the latest digital tools (e.g. GPT-4o) to undertake four main tasks