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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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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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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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. The initiating secondary genetic changes causing overt clinical disease that progresses to metastasis remains unknown. Metastasis is thought to be independent to tumorigenesis. Metastasis is a highly complex
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into their structure. However, we don’t yet know how to design these complex printed parts and we are still developing new leading-edge materials to grant them new capabilities. Advantages: In this PhD studentship, you
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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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PhD in the Engineering Hydrogen NetZero (EnerHy) CDT which is a new EPSRC-funded Centre for Doctoral Training (CDT) focusing on research and training in the areas of Hydrogen and Wind Energy. The
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable