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at experimentally informed microstructural features. You will combine first-principles modelling and machine-learning approaches to develop predictive simulations of hydrogen behaviour in compositionally complex Fe
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will be to quantify how mixing aircraft with strongly differing performance characteristics affects safety, efficiency and capacity, and to develop the metrics and models needed to make those effects
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biogeochemical processes that govern their behaviour. Job description The PhD candidate will develop and analyse new process-based mathematical models to improve our understanding and predictive capability
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combining advanced experiments with multiscale modelling, CIRHY enables reliable, sustainable steels for future infrastructure and industry. The project was granted by the Dutch national funding agency NWO in
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ice, using a framework consisting of an ocean Large Eddy Simulation (LES) and a Discrete Element Model (DEM) of sea ice. Results from these simulations will be validated against a combination of in-situ
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have: MSc in engineering or similar discipline by the start date of the position Experience with mechanical modeling and simulation Experience in computer programming/scripting (e.g., C++, Python, Matlab
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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different scenarios; implement and validate simulation models for system analysis, scenario evaluation, and future optimization; collaborateclosely with researchers, industrial partners, and fellow PhD
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-resolved simulations. In case a fluidized bed is chosen, a traditional Eulerian Two-Fluid model (TFM) will be compared with a novel Lagrangian Continuous Particle Model (CPM). Initially, engineering
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design rules to understand their chemistry and physics. You will combine coarse-grained and atomistic simulations with surrogate models and experimental insights (with Dr. Baumgartner) to understand