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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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or second-class honours degree in engineering, physics, mathematics, computer vision, or a related field. Interest or experience in computational modelling or coding—beneficial but not required. A
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responds to the vision of the programme and the four example PhD topics below. [S(1] https://www.blueskeye.com/ [S(2] https://www.nottingham.ac.uk/computerscience/work-with-us/somabotics-at-nottingham.aspx
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University Technology Centre (UTC) in Manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a 3-year PhD program in partnership with the UK Atomic Energy
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programme in, and a personal PhD proposal that responds to the vision of the programme and the four example PhD topics below. [S(1] https://www.nottingham.ac.uk/computerscience/work-with-us/somabotics-at
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algorithms, have excelled in tasks like computer vision, image recognition and large language models (LLM). However, their reliance on extensive computational resources results in excessively high energy
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PhD Studentship: Secure By Design Datasets – Distillation and Privatisation for Future Collaboration
and Signal Processing at the University of Surrey. This is the largest such UK institute and is ranked 1st for Computer vision research in the UK and 3rd in Europe (csrankings.org). The supervisory team
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automotive and motorsport courses at master’s level, and engaging in academic research and commercial consultancy. Interests are wide-ranging from mechanics and materials through to computer vision and self
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to undertake a PhD, specific motivation to undertake a PhD as part of the Somabotics programme in, and a personal PhD proposal that responds to the vision of the programme and the four example PhD topics below
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wind turbines are pivotal in driving the global transition to renewable energy; however, maintaining these critical assets poses substantial challenges. Advances in computer vision and deep learning