40 systems-science-"https:" "https:" "https:" "UCL" PhD positions at Cranfield University
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sampled. This PhD study will address this research challenge. Cranfield is the largest academic centre for postgraduate studies in Science and Technology in the UK. Focused on developing applied research to
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including the Ground Operations Laboratory in the Digital Aviation Research and Technology Centre (DARTeC), and the suite of facilities in the new Cranfield Hydrogen Integration Incubator (CH2i
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years EligibilityUK, EU, Rest of world Reference numberSATM450 About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university that is a
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to discover the fundamental mechanisms responsible for damage and deformation. About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university
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nutrient removal with biodiversity benefits. Optimising these systems is critical to enhance their environmental performance, support regulatory compliance, and contribute to resilient, low-carbon water
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Are you passionate about developing novel research and keen to shape the future of energy transfer technologies in areas such as, forensic science and Uncrewed Aerial Systems (UAS). We
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support from leading experts in Advanced Sensor Technology Research Group and Environmental Assessment Facilities at Cranfield University. This fully funded studentship is part of the Connected Waters
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, Sustainability Studies, Business (with a focus on environmental risks), Water or Civil Engineering, or other related social science degrees. It is essential that candidates have experience of, or a good
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This is a self-funded PhD position to work with Dr Adnan Syed in the Surface Engineering and Precision Centre. The PhD project will focus studying high temperature corrosion mechanisms in details
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap