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into its latest Ryzen processors, unlocking new possibilities for on-device AI acceleration. This project aims to maximise the potential of AMD’s cutting-edge hardware for healthcare computer vision
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
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position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement
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, including Machine Learning & Artificial Intelligence, Colour & Imaging, Computer Vision, Graphics, Data Science, Health Computing, Computational Biology, Cyber Intelligence and Networks. We collaborate with
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computer interaction in this context). This work will contribute to the empirical co‑design and testing of principles guiding the development and deployment of AI systems for assisting judicial decision
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efficient power electronics, clean energy generation and conversion, radically more powerful processors for artificial intelligence, electrification of transport and the explosion in space technology
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perspectives in psychology, education, computer sciences, law, and philosophy. Four WPs address citizen-empowerment-scenarios (CES) in healthcare, mobility, public governance, and healthy living. Each PhD
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perspectives in psychology, education, computer sciences, law, and philosophy. Four WPs address citizen-empowerment-scenarios (CES) in healthcare, mobility, public governance, and healthy living. Each PhD
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to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative