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approach towards artificial intelligence that uses the natural dynamic behaviour of physical systems (such as light and electronics) to process information efficiently. You will work at the intersection
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they would be integrated within production facilities. Excite your interest in creating manufacturing process models with a view to creating more sustainable aircraft parts. This project is extremely well
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electronics) to process information efficiently. You will work at the intersection of mathematics, physics, electrical engineering and AI, helping to develop a theory that explains how and why these systems
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sustain the widespread adoption of electrical vehicles in an environmentally friendly and ethical way. A radical approach to how electrical motors is developed, combined with emerging material technology
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student to revolutionise electrical machine design and development based on programmable 3D electrical steel technology enabled by advanced manufacturing processes and emerging magnetic materials
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Area Engineering Location UK Other Closing Date Thursday 30 April 2026 Supervisors: Dr Yaoyao Zheng , Prof. Hao Liu , Dr Omid Saghafifar (Remedium ) Programme Length: Four years Contract Type: Full
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Closing date: 8 May 2026 University of Nottingham in collaboration with SHD Composites Start date: 1 October 2026 The University of Nottingham is seeking an outstanding and highly motivated
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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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DigitalMetal in the Faculty of Engineering, which conducts cutting edge research into cutting-edge technologies and AI to revolutionise metals manufacturing. Vision We are seeking a PhD student who is motivated
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steel technology enabled by advanced manufacturing processes and emerging magnetic materials for applications across automotive, aerospace, and power generation. Starting from modelling and parametric