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This 3.5 year PhD project is fully funded for UK students. Your tuition fees will be paid and you will receive a tax free stipend set at the UKRI rate (£20,780 for 2025/26). We expect
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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applications, facilitating the transition of image-based measurement methods from laboratory research to clinical practice. Digital Image Correlation (DIC) is a well-established, non-contact optical technique
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testing) to understand and tailor the physical and chemical interactions within these complex structures. Cranfield University is internationally renowned for its research into materials for extreme
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for Additive Manufacturing research group (CfAM). The student will work in world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics
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world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and materials science. PhD project description: Responsive 3D
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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The Structural Battery Company, a high-tech manufacturer of EV batteries. Building on Cranfield’s previous APC-funded CERABEV successes using epoxy-based systems with intumescent ceramic phases, this project
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simultaneously, useful for printing functional devices. Discovering the interactions of these materials and how to leverage this advanced manufacturing process will open new opportunities: devices with variable
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subsequent precipitation hardening process. In addition, promoting a circular economy in the aluminium industry by increasing recyclability and using more recycled aluminium is essential for saving resources