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, and Internet-of-Things / Industry 4.0 technologies. Knowledge of computer science principles and modern AI approaches in computer vision and/or time series analysis is a plus. The position requires
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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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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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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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. Candidates must have a strong motivation for research and excellent programming skills. Expertise of developing computer vision and machine learning algorithms would be desirable, with an interest in image
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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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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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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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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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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