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PhD at the Forefront of Computational Solid Mechanics and Machine Learning School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application
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oscillations and BSM processes. This will involve taking a lead role in developing dedicated software frameworks, including the implementation of machine learning techniques. Ultimately, the software will be
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theoretical physics, quantum computing, or machine learning and have completed or be in the final stages of a PhD in this or a related discipline. Main duties and responsibilities Design and analyse quantum
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greener transportation and energy. Building on recent advances, the successful candidate will use a powerful combination of dynamical systems theory, optimisation, DNS and machine learning to model and
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experience of treatment. The overarching aim of the project is to use machine learning methods to understand why many people who are referred for treatment will drop out prematurely. To do this, two studies
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The design and testing of sounding rockets for hypersonic research School of Electrical and Electronic Engineering PhD Research Project Directly Funded UK Students Dr Alistair John Application
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Machine Learning Approaches. You will have access to the excellent training opportunities at the University of Sheffield, and will spend time on site at Procter and Gamble. A range of highly desirable
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of acoustic wave propagation in moving fluid and physics-based machine learning (ML) methods. Support experimental design in the laboratory, carry out data processing and to use the experimental results
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in the world and will develop skills in machine learning, observational and theoretical astrophysics. For more information on this project please contact s.littlefair@sheffield.ac.uk Information
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and has a large group of collaborators. You will be joining a great team of supportive and social PhD students working in a high-quality research environment. Learn More: The Dynamics Research Group