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scenarios as typically encountered by UK mountain rescue teams and apply innovative biomechanical analysis using Bournemouth University ’s in-vivo 3D motion tracking technology to determine residual motion of
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2025. Encouraged by the continuing success of modern machine learning (ML) techniques, researchers have become ambitious to develop ML solutions for challenging science and engineering problems with
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, engineering (e.g.: mechanical, electrical, electronic, materials) or a related subject. A relevant master’s degree and/or experience in the use of wearable technology will be an advantage but not essential
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Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a mathematical model for obsolescence modelling for railway signalling and telecoms
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Department/Location: Department of Engineering, Central Cambridge We are seeking a highly motivated Research Assistant/Associate to join EPSRC and industry funded Digital Roads (DR) Prosperity
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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DEPARTMENT OF HEALTH TECHNOLOGY AND INFORMATICS Research Assistant Professor in Medical Laboratory Science / Biomedical Science / Medical Imaging and Radiation Science / Medical Physics / Medical
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interdisciplinary team working on the development of cross-platform alignment technologies that integrate material science, process engineering and sustainability analysis to deliver scalable solutions for circular
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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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PhD Studentship: Revolutionising Litz Wire Development for Next Generation Ultra-High Speed Propulsion Motors The Manufacturing Technology Centre UK, and University of Nottingham This project offers