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runaway models and numerical methods in OpenFOAM. Design and optimize computational frameworks for high-performance simulation of reacting flows and battery safety phenomena on modern GPU architectures
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-driven approach for optimizing the growth of semiconductor materials by combining machine learning with a physics-based understanding of the growth process. Doping and processing of ultra-wide bandgap
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and shared cleanroom facility for the production of materials and components at the nanoscale. The Division has a strong commitment to undergraduate education, not least in the Master's programme
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