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Start date: 28/09/2026 Fee status: UK Duration *: 4 years 1st Supervisor: Dr Simon Jude 2nd Supervisor: Dr Robert Grabowski This funded PhD studentship is an exciting opportunity to conduct new
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
We are pleased to announce a self-funded PhD opportunity for Quantitative assessment of damage in composite materials due to high velocity impacts using AI techniques. Composite materials, such as
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This funded PhD studentship is an exciting opportunity to conduct new social-ecological research on perceptions of urban blue space. Despite often appearing to be natural systems, urban blue space
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engagement with industry, data-driven environmental decision-making and applied modelling experience directly relevant to careers in academia, consultancy, regulatory science, conservation NGOs and
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, environmental science, urban sustainability, geospatial analysis, or quantitative modelling. We particularly welcome applicants who are excited about integrating ecological understanding with data-driven methods
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This fully-funded PhD research opportunity, supported by EPRSC Doctoral Landscape Awards (DLA) and Cranfield offers a competitive bursary of £22,000 per annum, covering full tuition fees. This PhD
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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
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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Join us for this exciting self-funded PhD studentship on " Development of Sustainable and Cost-Effective Coatings to Mitigate Battery Thermal Runaway Propagation" in collaboration with
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, robotics, microbiology, environmental science, chemistry, physics or data science. Applications would be keen to blend hands‑on experimentation with advanced analytics to create low‑carbon, nature‑based