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Field
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programme aims to advance fundamental understanding of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key
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of the following: numerical methods, high-performance computing (HPC), Computational Fluid Dynamics (CFD), applied mathematics, physics, engineering or subsurface flow modelling. Enthusiasm
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12 Dec 2025 Job Information Organisation/Company Maastricht University (UM) Research Field Computer science » Modelling tools Computer science » Programming Engineering » Biomaterial engineering
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farm management through innovative sensing technologies, advanced modeling, and intelligent automation. This PhD project contributes to PhenoRob’s initiative to develop digital twins, i.e., high-fidelity
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling
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for efficient last-mile deliveries with a focus on climate and flexibility. Using advanced modeling and data analysis, you’ll create solutions that make final deliveries smarter and more sustainable. Your work
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) machine learning. The project will focus on one or a combination of the following focus areas, tailored to the candidate’s expertise and interests: Developing numerical models for the coupled mechanical
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We invite applications for a fully funded PhD position in the field of numerical modelling of iron electrodeposition, i.e., multiphase flows involving phase change, using fully resolved CFD methods
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mineral and metal-bearing raw materials more efficiently and to recycle them in an environmentally friendly way. The Group Geometallurgy and Particle Based Process Modelling is looking for a PhD Student (f
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the development of a more practical numerical model (e.g. Delft3D) that will be developed within another SOURCE PhD project to predict nourishments’ lifetime, spreading and impacts on coastal state indicators