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models. The project will include multiphysics learning, uncertainty quantification, and closed-loop design frameworks integrating real experimental feedback, with the goal of creating robust and reliable
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prediction, uncertainty quantification) and analysis of data from monitoring systems or industrial processes. • Knowledge of hybrid modelling approaches combining physics-based models (e.g., FEM, fracture
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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of spectrophotometric pH measurements in seawater. Marine Chemistry, 259: 104362. https://doi.org/10.1016/j.marchem.2024.104362 . analytical chemistry; marine chemistry; carbon dioxide; uncertainty quantification
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Lehrstuhl für Angewandte und Computergestützte Mathematik | Aachen, Nordrhein Westfalen | Germany | 6 days ago
links to the groups of numerical analysis at IGPM and uncertainty quantification at UQ. Some of our PhD students and Postdocs are associated with the research training group Energy, Entropy and
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for simulation and modeling of wave dynamics, and for uncertainty quantification of extreme events. The project will combine stochastic mathematical models of wave physics with advanced computational methods
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Description Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and
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, claims data, registries, pragmatic clinical studies, and other real-world data sources. Areas of methodological interest may include uncertainty quantification, conformal inference, causal inference
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participation, control strategies, lifetime extension) Risk, uncertainty quantification, and value-of-information perspectives for operational decision making System representations (e.g., structured model
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experiments using high-level programming languages (e.g., Python, MATLAB, R, or Julia). Curate and integrate experimental data to calibrate and validate models, including parameter estimation and uncertainty