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PhD Studentship: Quantum Algorithms for Nuclear Level Densities Atomic nuclei have a rich structure, with heavy nuclei having many excited states – of order thousands or higher. Knowledge
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underexplored. To this end, the project will explore the application of the next generation of deep learning algorithms, e.g. self-supervised learning techniques, particularly suited to infrastructure
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. Bayesian networks and related machine-learning methods will be used to calculate cross-section probability density functions in a much faster way, enabling the combination of multiple probability
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