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for Paediatric Echocardiography Supervisor Names: Dr Patrick McAllister This PhD project will develop and evaluate explainable, domain-adaptive deep learning approaches for image- and video-based classification
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an international visit to the partner, Texas A&M Transportation Institute (TTI), where the PhD researcher will analyse the carbon footprint of transporting fibre crops from farm to processing facilities. This unique
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rework, waste, and delays. This project tackles that challenge by developing camera-based process monitoring system that observes the weld in real time, detects and predicts anomalies as they emerge, and
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, climate control, and irrigation systems, poses critical challenges to its economic viability and environmental sustainability. This PhD project aims to design, develop, and optimise a climate-smart, net
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how the artificial joint is positioned. Small changes in placement can alter how the joint moves, the forces it experiences, and ultimately how long it lasts. However, current imaging and planning
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difficult to interpret and require vast amounts of data to perform well. This PhD will investigate how AI can become more adaptable, efficient, and understandable by integrating people directly into the
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high powered imaging techniques including confocal, SEM and TEM. Important Information: Applications for more than one PhD studentship are welcome, however if you apply for more than one PhD project
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Summary This PhD investigates how regenerative textile systems can be developed through design-led, field-to-field models that integrate fibre cultivation, land stewardship, and community making
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designed to augment human intelligence and well-being. This research aims to enable this paradigm shift by upgrading existing Industry 4.0 robotic systems to meet Industry 5.0 standards through
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/backdrops), Post-production VFX (digital extension and repair). Typically spawned from the same initial digital footprint, these processes tend to drift apart. The original high-value digital assets