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of algorithmic systems. The research will investigate how clinicians interact with automated and machine learning–based decision-support systems, with a particular focus on cognitive workload, trust, situational
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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on developing the simulation models, data models and algorithms required to enable connected cross-disciplinary design and optimisation, laying the foundations for more integrated and intelligent engineering
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algorithms. This is an exciting multidisciplinary PhD project that promises to make cutting-edge advances in all research areas involved. Aim This project combines practical hands-on optics experimentation
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. Expect close collaboration with industrial experts and the opportunity to see your algorithms influence aerospace and other high-value manufacturing sectors. Funding and eligibility 3-year, full-time PhD
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. Expect close collaboration with industrial experts and the opportunity to see your algorithms influence aerospace and other high-value manufacturing sectors. Funding and eligibility 3-year, full-time PhD
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, memory, and energy requirements. The successful candidate will explore novel algorithms and model-design strategies that allow AI systems to operate effectively on edge devices, clinical environments
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algorithms that allow robots to refine their control strategies based on observed human behaviour. Collaboration: The project will benefit from extending existing collaborations between the University