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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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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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Salary Range £31,637 - £37,174 per annum School/Department Computer Science and Mathematics Liverpool John Moores University (LJMU) is a distinctive, unique institution, rooted in the Liverpool City
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
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and colleagues located across the 4 nations of the UK. HDR UK’s mission is to unite the UK’s health data to enable discoveries that improve people’s lives. Its 20-year vision is for large-scale data and
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and a construction and testing capability up to 5MW Vision This project aims to leverage the electric propulsion hardware developed in the EU-funded €40M NEWBORN – “NExt generation high poWer fuel cells
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approximately 2500m2 of research space and a construction and testing capability up to 5MW Vision This project aims to leverage the electric propulsion hardware developed in the EU-funded €40M NEWBORN – “NExt
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Vision 2028 strategy underscores our commitment to reshaping education for the benefit of all. We empower students from all backgrounds with the skills and opportunities to excel in today’s dynamic world