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Field
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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the genetic factors influencing changes in brain structures, using brain imaging, computational and statistical methods of network science. Project Aim: The aim of the project is to uncover the complex
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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mitigation system. Understanding the process of droplet impact and freezing dynamics at high airspeeds, on textured and non-textured surfaces is critical to deciphering the physics behind ice adhesion and
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Ultrafast lasers drive innovations from quantum technology to medical imaging, yet controlling femtosecond pulses remains a major challenge. Metamaterials are artificial structures with
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propellant space propulsion systems. A significant limiting factor of hybrid propulsion systems is the continuous change in surface area of the propellant grain during the combustion process. This changing O/F
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establishment and growth of trees in newly planted woodland ecosystems. Despite their critical ecological function, the specific roles of ectomycorrhizal fungi in facilitating afforestation processes remain
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developed through large programmes of research. You will aim to develop and validate a computational testing process, which can include patient variability for the biomechanical assessment of fusion devices