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M Fallon

Professor at Department of Engineering Science

University of Oxford

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United Kingdom

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Research Interests

Artificial Intelligence

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Mechanical Engineering

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Electrical Engineering

10%

Robotics

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Computer Science

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Semantic Segmentation

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Positions1

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M Fallon

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University of Oxford

PhD in Long-Term 3D Change Detection of Industrial Facilities (RAINZ CDT, Robotics & AI for Net Zero)

The EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero (RAINZ CDT) is a collaborative initiative between the University of Oxford, University of Manchester, and University of Glasgow, aiming to advance the use of Robotics and Autonomous Systems (RAS) in the UK’s energy sector. This PhD project, based at the University of Oxford’s Department of Engineering Science, focuses on long-term 3D change detection in industrial facilities, particularly nuclear sites, to support remote inspection, maintenance, and decarbonisation efforts. Students begin with a taught MSc year at the University of Manchester, followed by three years of PhD research at Oxford. The research will leverage cutting-edge 3D visual sensing technologies, including implicit neural rendering (NeRF, Gaussian Splatting) and Geometric Foundation Models (MapAnything, VGGT), to infer 3D changes using camera-based sensing. The project will also involve multi-session visual SLAM and semantic segmentation to build scalable, 4D (3D plus time) representations of industrial environments, enabling precise monitoring of facility conditions and detection of subtle changes such as crack growth or corrosion spread. Previous work at the Oxford Robotics Institute has demonstrated real-time 3D LIDAR mapping (VILENS) in nuclear facilities, but this project aims to surpass LIDAR’s limitations by identifying object-level changes and achieving finer detection granularity. The research is highly interdisciplinary, integrating robotics, computer science, and engineering, and is designed to address real-world challenges in asset monitoring and maintenance for Net Zero goals. Successful applicants will join a cohort-based training programme, gaining expertise in teamwork, sustainability, industrial engagement, and commercialisation. The studentship offers comprehensive funding: tuition fees at the Home rate, a UKRI minimum stipend (£20,780 for 2025/26, with annual increases), a Research Training and Support Grant for travel and consumables, and additional funding for CDT activities. Home applicants to Cohort 2 receive a £10,000 annual stipend enhancement. Limited international studentships may be available, with potential fee waivers discussed during interviews. Eligibility requires a First or strong Upper Second-class honours degree (2:1 with 65% average) in Engineering, Computer Science, Physics, Mathematics, or related disciplines, plus programming experience. The CDT values diversity, inclusion, and accessibility, offering flexible working arrangements and a selection process designed to minimise bias. Applications should be submitted via the RAINZ CDT website. Informal enquiries are welcome at [email protected]. The application deadline is February 13, 2026. For more details, visit the project page: FindAPhD Project Link .

1 month ago