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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific
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inference pipelines for soft biomechanical systems, including differentiable physics engines, to support interpretable analysis, parameter estimation, sensitivity studies and uncertainty quantification. By
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field, with a strong track record in numerical modelling, mathematical analysis and the development of computational methods for complex systems Additional requirements In addition to your CV and your
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