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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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Location: Students will be based at the CREWW building on Streatham Campus in Exeter. Flooding is the most common natural disaster, impacting billions worldwide. Natural Flood Management (NFM), a
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complex metal structures. This opportunity is centred around improving manufacturing productivity with advanced laser-matter interactions control and optimisation. The PhD will advance our comprehension
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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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to achieve complex and customisable micro-robots to provide personalised healthcare solutions. Advantages: This studentship will take place in world-leading research laboratories for additive manufacturing
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mechanical and chemical properties; fully 3D-printed electronics; and devices with mechanical or electrical responses encoded into their structure. However, we don’t yet know how to design these complex
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necessary to 3D-print the next generation of medical micro-robots targeting drug delivery, exploiting combinations of functions to achieve complex and customisable micro-robots to provide personalised
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dispersion - and develop a system to disperse the particles. The project will explore the options for dispersion and the options for nozzle design and whether substantial additional air supply is needed
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crucial role in determining mechanical properties, yet integrating this information into predictive models is complex. This project will focus on developing a combination of advanced machine learning and
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dispersion - and develop a system to disperse the particles. The project will explore the options for dispersion and the options for nozzle design and whether substantial additional air supply is needed