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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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THR demand in younger patients expected to increase fivefold by 2030, revision surgeries will also rise. To improve implant positioning, image-guided navigation is increasingly used in complex THR
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Overview: As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by
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respond over time (e.g. changing shape), controlled by the arrangement of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug
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-printed functional devices interact with their environment, responding to stimuli (temperature, light, etc.), and “4D-printed” devices respond over time (e.g. changing shape), controlled by the arrangement
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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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, such as compilers, is an exceedingly complex task that often requires investments of hundreds of millions of dollars. This project aims to explore the extent to which LLMs can be harnessed to assist in
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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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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