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for the power plant. We have an opening for a candidate with an interest in the application of machine learning to particle physics simulation and proven skills in software development. The student would
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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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-driven techniques, such as machine learning approaches, will enrich the scope of the project. Students engaged in this project will potentially have the chance to collaborate with industry partners in
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challenges faced in the real-world via a Systems Thinking approach. You will learn about the wider challenges of research and innovation within the Defence & Security sector. Entry Requirements This PhD
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PhD Studentship: Centre for Doctoral Training in Composite Materials, Sustainability and Manufacture
predicting the effect that these defects have on structural performance. The occurrence of defects is a complex problem involving many factors. A combination of statistical tools and advanced machine learning
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, including machine learning, to simulate CFRP's complicated response to various loading and environmental conditions. The development of the tools will require significant amount of computer programming using
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a strong background in Computer Science, Engineering, Maths or Physics, and preference would be given to those with a good understanding of computer vision and deep learning. It is essential to have a
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developments in artificial intelligence (AI), machine learning (ML) and microelectronics have enabled drones to work even more efficiently, enabling them to address emerging demands in several sectors including
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PhD Studentship: Centre for Doctoral Training in Composite Materials, Sustainability and Manufacture
predicting the effect that these defects have on structural performance. The occurrence of defects is a complex problem involving many factors. A combination of statistical tools and advanced machine learning
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process efficiency improvements and enable prediction across scales for a given biological process. The PhD project will develop, construct and apply Machine Learning techniques to the process data