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based on Machine Learning (ML) emulators have taken the weather predictions research by storm, as they run faster and use less energy than traditional approaches: numerical models based on physical
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predictive control, optimization-based decision frameworks, and data-driven performance modelling. The overall goal is to develop computational methods that enable efficient and intelligent operation of wind
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for developing reliable predictive models and ensuring safe and robust component design. This position is part of the CastAl project, which aims to identify the mechanisms governing stochastic fracture in HPDC
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long-term goal of our group is to develop a self-consistent model of FGFs and other lightning-generated high-energy radiation, then using radio and optical predictions from this model to compare against
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on the combination of Reinforcement Learning (RL) and Model Predictive Control (MPC). It will build up upon the work done at ITK on the topic. Several research focuses are considered: verification pathways in RLMPC
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].. [1] Salomonsen, C. "A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F]FDG PET imaging. " EJNMMI Research, 2026. [2] Thomas, S
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and increased uncertainty in life and non-life insurance modelling. data-driven prediction of insurance premiums and associated quantification of uncertainty. Qualifications and personal qualities
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27th April 2026 Languages English English English The Department of Structural Engineering has a vacancy for Two PhD positions in “Micromechanics-based modelling of ductile failure in high-strength
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
microstructure evolution during extrusion is critical for controlling final mechanical properties and surface appearance of extruded profiles, yet quantitative predictions remain challenging due to the complexity
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., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves