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Field
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-informed / simulation-aware modeling Efficient algorithms for design-space exploration (e.g., surrogate modeling, Bayesian optimization, differentiable programming) Hybrid approaches combining data-driven
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disturbances or cyberattacks, such as sensor manipulation, electromagnetic interference, or injected faults, can affect the behaviour of power electronic systems. Developing data-driven models that capture how
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(mainly developedat UEE). In particular the scientific program consists of the following tasks: – Modeling dissolution and precipitation of carbonate minerals within the caprock driven by diffusive and/or
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17 Mar 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Modelling tools Geosciences » Geology Geosciences » Hydrology Researcher
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to study and predict. In this four-year SNF-funded project, you will develop data-driven, multiscale simulation methods that combine computer simulations, machine learning, and surrogate models to explore
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engineering excellence needed for the aerospace sector. In this PhD, high-fidelity two-phase Computational Fluid Dynamics (CFD) methods will be used to model complex and fundamental cryogenic hydrogen flows
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chemistry or materials science. Experience in surface science and hydrogen technology is of advantage. The ideal candidate has an independent, target- and solution-driven work attitude, inter- and
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on the modelling of transmission dynamics and risk assessment of mosquito-borne arboviruses with the potential to invade the EU. Addressing this challenge requires an interdisciplinary approach, combining
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: • Experience of applying CFD to a complex problem • Appreciation of meshing requirements for aerodynamic simulations • Experience with machine learning or data-driven modelling techniques Funding
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turbomachinery design is increasingly the primary bottleneck. Within the next decade, this workflow will be largely replaced by data-driven inverse design models, enabled by the growing availability of high