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have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering
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and travel Requirements The candidate should have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related disciplines. Skills in numerical tools and programming
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background in Computer Science, Mathematics. Students with interests in machine learning, deep learning, AI, uncertainty quantification, probabilistic methods are encouraged to apply. For eligible students
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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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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in a degree, ideally at Masters level, in an Engineering subject, Physics, Mathematics, Computer Science or other quantitative background. Knowledge in fluid mechanics, ocean waves, numerical methods
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PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work independently
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Application deadline: All year round Research theme: Applied Mathematics, Mechanical and Aerospace Engineering, Fluid Dynamics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5
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equivalent in a subject relevant to the proposed PhD project (such as mathematics or theoretical physics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the
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, Aerospace and Civil Engineering at the University of Sheffield, and embark on a transformative PhD project funded by John Crane Ltd, a global leader in engineering technology. What’s the Project About