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graduated at Master’s level in machine learning, statistics, computer science, fluid mechanics, or a related area that is considered relevant for the research topic of the project, or have completed courses
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numerical analysis, computational fluid dynamics, and uncertainty quantification with diverse applications. Our group maintains active collaborations with other divisions at Linköping University and broader
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. Computational tools for simulating such processes - both traditional based e.g. on computational fluid dynamics and more recent based on AI/machine learning - constitute fundamental scientific domains that act as
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