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reactors, with particular emphasis on statistical methods, uncertainty quantification and machine learning to improve the accuracy and computational efficiency of fuel-performance analyses. The work
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/research/air-water-and-landscape-science ). Duties The PhD project will focus on uncertainty quantification in modelling flow and solute transport in fractured rocks. The work will include numerical
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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, synthetic data or data-driven decision support uncertainty quantification, robustness, variation simulation or tolerancing CAD/CAE integration, geometry assurance or quality data automation, control, 5G/6G
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causal inference, integration of heterogeneous data sources, uncertainty quantification Work with a wide range of data types, for example dietary records, biomarkers, omics data, registry data, and sensor
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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization
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. Experience applying machine learning to networking problems, for example, reinforcement learning, graph neural networks, or uncertainty quantification. A track record of publications in leading networking
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. Experience applying machine learning to networking problems, for example, reinforcement learning, graph neural networks, or uncertainty quantification. A track record of publications in leading networking
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. Experience with atomistic simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification