37 software-engineering-model-driven-engineering-phd-position-"https:" PhD positions at Cranfield University
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models such as Random Forest and Neural Networks to help understand and predict pairwise interactions between pollinators and plant species. - Software Engineering: integrate models into a standalone
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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. Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has recognised 81
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This PhD studentship covers fees and stipend for a home (UK) student to investigate how urban blue networks can be optimised to enhance ecological resilience and community wellbeing. The project
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
for automated, data-driven diagnostics, integrating AI with high-resolution imaging and sensing offers a transformative solution. AI models can learn to recognize subtle damage patterns, enabling faster, more
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mitigate the risks that contaminants pose to water security, human wellbeing, and biodiversity. This funded PhD studentship will work with conservation charities and citizen scientists to develop and
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Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2014 (REF) has
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engineering, digital technologies, and systems thinking. The university’s strong reputation for applied research and its focus on technological innovation ensure that this project will be well-supported, with
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This exciting fully funded PhD, with an enhanced stipend of £25,726 per annum (with tuition fees covered), is sponsored by Anglian Water and EPSRC. It directly tackles one of the central challenges
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits