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the atomic-scale competition between copper and silicon at grain boundaries and oxide interfaces, delivering atomistic insights directly relevant to improving the recyclability and processability of both
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-generation circular steelmaking. Using advanced atomistic modelling techniques, you will unravel the atomic-scale competition between copper and silicon at grain boundaries and oxide interfaces, delivering
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including dynamical and cosmological horizons, gravitational entropy, Noether charge methods, holographic coarse-graining, chaos, black hole heat engines and quantum field theory in curved space-time. These
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holographic systems out of equilibrium, with possible topics including dynamical and cosmological horizons, gravitational entropy, Noether charge methods, holographic coarse-graining, chaos, black hole heat
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capabilities in specialized domains with limited supervision. Potential research directions include, but are not limited to: Adaptation and specialisation of visual foundation models; Fine-grained visual
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to: Adaptation and specialisation of visual foundation models; Fine-grained visual understanding and representation learning; Self-supervised and data-efficient learning; Transfer learning and knowledge reuse
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lifetimes of spins on surfaces. This approach combines electronic states obtained via a periodic quantum embedding (i.e., equation-of-motion coupled-cluster in periodic DFT, pbcEOM-CC) with a coarse-grained