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of Artificial Intelligence (AI) to address such challenges offers an opportunity. This PhD will investigate how adopting agentic AI can improve supply chain resilience. The project aims to develop and empirically
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, demonstrating how ICWs contribute to biodiversity, water quality, and regulatory compliance. Outputs will inform low-carbon, resilient infrastructure planning and support wider adoption of nature-based solutions
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relation to water reuse. They will also directly inform emerging water sector strategies and regulator discussions around water reuse, to help support more widespread adoption of water reuse while managing
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
carbon fibre-reinforced polymers (CFRPs), are increasingly adopted in structural applications due to their superior strength-to-weight ratios and fatigue resistance. However, their layered, anisotropic
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Start date: 28/09/2026 Funding Sponsored by Cranfield University, this full-time PhD Studentship will cover the PhD programme fees and provide an annual bursary of £20,780 (tax free) for three years
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detection of chemical and microbial contaminants in rivers. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research
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system. This project will focus on improving the intake aerodynamic design systems in terms of design optimisation as well as computational modelling. Entry requirements Applicants should have a first or
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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at Cranfield University within a supportive, cross-disciplinary environment spanning energy systems engineering, computational modelling, bioinformatics and food safety science. The studentship is funded by