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within CFD modelling, with a particular focus on the projects MetNH3Energy and ACE Water. You will be involved in both independent and collaborative research activities in Europe in close interaction with
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experiments, CFD, and reduced-order models to develop design tools that are sufficiently fast for iterative early-stage development while still capturing the relevant physics. In teaching, you will contribute
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pragmatic, iterative mindset - prioritising what works empirically and is testable over purely theoretical correctness. Valued: Experience with high performance computing (HPC). Prior exposure to mass
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, interdisciplinary working environment In-house modelling, data processing and data assimilation expertise, software, and High Performance Computation (HPC) infrastructure Excellent scientific infrastructure
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scripting (R, Python) and programming. Experience with High-Performance Computing (HPC) environments and the management/analysis of large datasets. The ability to communicate effectively in English (both
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in Python, C++, MATLAB/Simulink, ROS, Gazebo or other simulation and robotics frameworks. Experience with CAD/CAE, CFD, digital twins, embedded systems or experimental data analysis is an asset