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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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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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. 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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(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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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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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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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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PhD Project: 3D-printing next-generation electro-actuators for soft robots and devices Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive