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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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, that consumers still enjoy. By developing novel, cutting-edge technological approaches including computer vision, machine learning and robotics, blended with consumer science, you will be at the forefront
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and challenging materials. Artificial Intelligence and Machine Learning techniques will be employed to analyse experimental data, enabling deeper insights and faster optimisation of the nozzle design
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also developing skills in data analysis and machine learning. This role offers a unique opportunity to grow as a researcher, contribute to high-impact publications, and shape the future of biomolecular
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Intelligence, Machine Learning, Software Implementation and Testing, and their applications in manufacturing, transport, healthcare and others. About You The position holder will teach core undergraduate and
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Intelligence, Machine Learning, Software Implementation and Testing, and their applications in manufacturing, transport, healthcare and others. About You The position holder will teach core undergraduate and
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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motivated PhD student to join our interdisciplinary team to help address critical challenges in high-speed electrical machine design for electrified transportation and power generation. Together, we will make
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Bezares (numerical relativity), Dr Stephen Green (gravitational waves, data analysis including machine learning, black holes), Dr Laura Sberna (gravitational waves, black holes, and environmental effects