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Field
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, and more reliable hybrid thermodynamic and data-driven predictive models The methods developed in this project will overcome current limitations in training data sparsity, quantification of model
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anomaly detection Bayesian methods and uncertainty quantification Graph Neural Networks (GNNs) Spatiotemporal data engineering Digital twins and simulation Demonstrated Applied AI for Healthcare and
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty
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statistical learning theory and probabilistic models; prior exposure to notions of robustness, resilience, or uncertainty quantification is an advantage. Mathematical maturity and experience with formal
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Computational Fluid Dynamics (CFD) has become indispensable for aerospace design, many important problems—including high-fidelity flow simulations, uncertainty quantification, and multidisciplinary optimization
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Experience in one or more of the following areas: object detection and segmentation, multi-object tracking, time-series analysis, probabilistic modeling and uncertainty quantification, real-time or streaming
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, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
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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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design optimisation, control, data-assimilation, uncertainty quantification, and multi-fidelity approaches is encouraged. The candidate is expected to collaborate with international fusion initiatives
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of analytics into production systems Knowledge of experimental design, uncertainty quantification, scientific machine learning, or digital twin methodologies Experience collaborating across national laboratories