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Motivation: Soft and flexible materials (e.g. polymers, hydrogels) have revolutionised many areas of science and technology ranging from flexible electronics to soft robotics. Scientists now predict
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engineering with an emphasis on developing and refining processes which must be compatible with large scale manufacturing. The successful applicants will expect to split their time between the Swansea Bay
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Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the defence Sector (source: the UK Atomic Weapons Establishment). Recent work by the group (leading to REF 4* rated outputs and several Keynotes) has...
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Supervisors: Dr Jun Jiang (Reader), Mechanical Engineering Department Deadline for application: 30/10/2025. Early submission is encouraged. Funding mechanisms: Fully funded by Imperial College, IDLA
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. The successful candidate will be based in the Mechanical and Aerospace Systems research group (previously known as G2TRC) within the faculty of Engineering and will be part of a supportive team of 50 researchers
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for aviation use. The successful candidate will be based in the Mechanical and Aerospace Systems research group (previously known as G2TRC) within the faculty of Engineering and will be part of a supportive
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Engineering, Mechanical Engineering or related subjects. Funding and Eligibility: UK only Key Information Supervisors: Professor Tony McNally
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Discipline: Engineering & Technology, Materials Science, Mechanical Engineering Qualification: Doctor of Philosophy in Engineering (PhD) This collaborative project between Jaguar Land Rover (JLR
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boundaries. This fully funded PhD scholarship is suitable for students with a background in Engineering Design, Smart Manufacturing, Aerospace Engineering, Mechanics, Computer Science, Mathematics, Life Cycle
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: This position is ideal for candidates with a background in civil engineering, structural engineering and mechanical engineering. Applicants should demonstrate: A strong interest in both experimental and numerical