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the Oxford Martin Programme. It is essential that you hold, or are close to completing, a PhD/DPhil in Earth Sciences, Geochemistry, Geophysics, Environmental Geoscience, Mineral Physics, Physical Chemistry
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, computational physics, quantum information, quantum computing, applied mathematics, computer science or a closely related discipline. Candidates who have submitted their thesis and are awaiting award may be
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Infrastructure Computer Vision Data Analytics for the Built Environment You should possess: A completed PhD in a relevant discipline. Strong research expertise in digital engineering and built environment research
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and Musculoskeletal Sciences (NDORMS) is part of the Medical Sciences Division and is the largest European academic department in its field, running a globally competitive programme of research and
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route to fertiliser production and improved food and energy security. You will work within a highly collaborative research environment, engaging with colleagues across Earth Sciences, Computer Science
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, or be nearing completion of, a PhD in Computer Science or a cognate field. The successful candidate must possess expertise in distributed AI/ML systems and computer networks. Good knowledge and practical
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to PhD level in an area related to Computer Science, the applicant will be proficient in software development, systems administration, networking and cloud. This is an invaluable opportunity to develop
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of Liverpool) with Professor Mark Green (Geography and Planning, University of Liverpool) and Professor Heather Brown (Health Economics, Lancaster University). Project partners include Oxford University, London
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strategies. About You You will hold a PhD in Materials Science, Nanotechnology, Applied Physics, Electrical Engineering, or a related discipline. You will have experience in 3D metamaterials or architected
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environmental conditions and material properties, in situ, through tracer development. You will be part of a highly collaborative programme working within the department of Physics and Materials Innovation