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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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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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computers”(under the UKRI Guarantee scheme). Topics include: - Quantum many-body dynamics - Quantum algorithms - Quantum-enhanced numerical methods - Quantum machine learning - Tensor Networks - Topological
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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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Subject area: Drug Discovery, Sustainability, Laboratory Automation, Microfluidics, Machine Learning Overview: This highly interdisciplinary 4-year funded PhD studentship will contribute to cutting
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly
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(CHF), tailored to complex geometries typical of fusion reactor cooling systems. Compile a comprehensive dataset of boiling parameters to support machine learning-based analysis of two-phase flow
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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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, 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