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Field
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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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includes areas such as statistical learning theory, high-dimensional statistics, causal inference, uncertainty quantification, fairness, and interpretability in AI. We encourage interdisciplinary research
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is to obtain imaging methods that are more robust and computationally efficient, while also providing a natural framework for uncertainty quantification and experimental design. A central question is
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experiments and theory into predictive injector-design tools. Analyze data with appropriate uncertainty quantification; maintain reproducible code, datasets, experimental records, and protocols; uphold
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. This position is designed for scientists with strong computational and quantitative training who are interested in agent-based modeling, network science, infectious disease dynamics, uncertainty quantification
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: • Develop and benchmark multimodal AI / foundation-model approaches for spatiotemporal forecasting. • Build reproducible AI training and evaluation pipelines, as well as uncertainty quantification
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, transfer learning, uncertainty quantification, multitask learning, or learning from sparse and expensive scientific data. Familiarity with atomistic or molecular-simulation software and interfaces, such as
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in interdisciplinary fields, knowledge of codes in related disciplines, such as thermal hydraulics, actinide chemistry, fuel cycle analysis, particle physics, or uncertainty quantification. A minimum
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knowledge; (d) develop reliability-aware diagnostic methods involving uncertainty quantification, confidence calibration, conformal prediction, out-of-distribution detection, and unknown fault recognition
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Qualifications Experience with graph neural networks, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification