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language models, multi-agent systems, reinforcement learning and knowledge evolution, evaluated using industry operational datasets. These positions offer an opportunity to advance autonomous decision-making
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checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC archives dating back
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methods with the ability to implement and evaluate machine-learning systems at scale. Candidates may come from topological data analysis, geometric deep learning, network science, statistical physics
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requirements. Acquire generic and transferable skills (including project management, business skills and postgraduate mentoring/supervision), subject to availability within the University. Research (specific