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Field
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connection with uncertainty or data science. Specific fields of interest include, but are not limited to, stochastic partial differential equations, optimal transport, gradient flows, uncertainty
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uncertainties. Knowledge of Bayesian approaches such as Gaussian process regression, particle filters, Bayesian networks, graph-based approaches. Probabilistic -based uncertainty quantification is also essential
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-dimensional data. Develop modular methods that incorporate domain-specific information into latent-variable models. Investigate methodological questions related to computation, identifiability, uncertainty
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of interest include, but are not limited to, stochastic partial differential equations, optimal transport, gradient flows, uncertainty quantification, model order reduction, data assimilation, optimal control
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limited to, stochastic partial differential equations, optimal transport, gradient flows, uncertainty quantification, model order reduction, data assimilation, optimal control, and their applications
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis. The
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methods and depth in one or more of generative modelling, reinforcement learning, Bayesian optimisation, active learning, uncertainty quantification, causal modelling, or optimisation in complex search
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variablemodels), efficient inference methods(e.g. sampling methods), uncertainty quantification, calibration, and probabilistic forecasting, as well as the interdisciplinary application of these methods
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-dominated parametrized problems, control, and uncertainty quantification. The start date is flexible and the initial appointment will be for one year with yearly extensions depending on performance and