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Location: Faculty of Science and Faculty of Engineering, University of Nottingham, UK Start Date: 1 October 2026 This PhD offers an exciting opportunity to explore reservoir computing, a new
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PhD offers an exciting opportunity to explore reservoir computing, a new approach towards artificial intelligence that uses the natural dynamic behaviour of physical systems (such as light and
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Location: University of Nottingham, Faculty of Engineering Start date: 1 October 2026 Application deadline: 14 May 2026 Project type: Collaborative PhD studentship (joint Academic-Industry
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collaboration with partners with modelling expertise. This PhD offers the opportunity to work at the interface of plant physiology, root biology, imaging and quantitative analysis. The student’s work will provide
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collaboration with partners with modelling expertise. This PhD offers the opportunity to work at the interface of plant physiology, root biology, imaging and quantitative analysis. The student’s work will provide
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tools that support the understanding of defect generation during forming. Identify state-of-the-art software and methodologies for modelling composite manufacturing processes and demonstrate how
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This is a 3.5-year full-time studentship and the successful applicant will receive a tax-free annual stipend and home tuition fees paid. Vision We are seeking a PhD student that is motivated in system
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their performance relative to current pragmatic industrial approaches. The successful candidate will spend at least 3 months during the PhD based within Siemens Digital Industry Software, receiving joint supervision
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commencing on the 2nd of March 2026 (online or in person, depending on the candidate’s location). The selected candidate will need to follow the regular PhD application process at the University of Nottingham
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, resourceful PhD candidate, with knowledge in aircraft power systems and IT skills in MATLAB/Simulink and other related software. Applicants should have achieved or be expecting to achieve a 1st or a 2:1 in an