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larger effort to map material performance limits and unlock untapped robustness in engineering alloys. You will: Develop and implement physics-based microstructural models to simulate damage and fatigue
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temperature within the engine environment. The aim of the proposed research is to develop modern primary atomisation models which better capture the atomisation physics associated with modern aerospace airblast
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deployments. Candidate Requirements Applicants should have (or expect to receive) a UK 1st class, 2:1 or equivalent in electronic engineering, physics, or a closely related discipline. Experience with
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communication. Entry requirements Applicants should hold or expect to achieve an equivalent of a first or second-class UK honours degree in materials science, physics, engineering, or a related discipline. The
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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transmission is a foundational technology for modern power systems, efficiently delivering electricity over long distances and enabling the integration of remote renewable energy sources. As renewable
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in Physics, Maths, Engineering, or a related discipline. Be familiar with differential equations and have some
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Department/Location: Department of Engineering, Central Cambridge A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on experimental investigations
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A 3.5 year PhD Engineering studentship under the supervision of Dr Evgeny Petrov . Blade vibrations in compressor and turbine bladed disks are one of the critical issues in designing gas-turbine