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physical wellbeing. We are committed to progressing the diversity and inclusion agenda, for example; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze
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; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working
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Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working Families, and sponsors of International Women in Engineering Day. We
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
) in a relevant discipline such as aerospace engineering, mechanical engineering, electrical engineering, computer science, applied mathematics, or a closely related field. Experience or interest in
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; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working
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with a background in mechanical, aeronautical, automotive, civil / industrial and/or software engineering (or similar) and/or mathematics and/or physics. The ideal candidate will have a solid background
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This is a self-funded PhD position to work with Dr Adnan Syed in the Surface Engineering and Precision Centre. The PhD project will focus studying high temperature corrosion mechanisms in details
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with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience
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Entry requirements Applicants should have a first or second-class UK honours degree or equivalent in a relevant discipline. This project would suit a student with engineering, physics, mathematics
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Applicants should have a first or second-class UK honours degree or equivalent in a relevant discipline such as engineering, physics and mathematics. Prior experience in fluid networks modelling is beneficial