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coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics
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numerical/computational modelling methods (e.g. discrete element method or finite element analysis) Strong programming skills Good written and verbal communication skills in English Considered an
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independently and in a team, and an interest in working with industry partners Willingness to do hands-on work underground and in the laboratory Basic programming ability in Python, MATLAB, R, or similar
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learning, particularly physics-informed or physics-constrained learning Programming and modelling skills (Matlab/Simulink, Python, C or other embedded-systems languages) Interest in embedded systems and
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mass transfer. Experience with microscopy, surface characterization, nanofabrication, or experimental instrument development is an advantage. Good data-analysis and programming skills (e.g., Python
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engineering, or a related field. Strong interest in doctoral research on audio deepfake detection, watermarking, source tracing, and generative AI. Good programming skills, preferably including Python and
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processing, estimation theory, or a related area Good mathematical and analytical skills Programming skills suitable for numerical simulation, signal processing, or experimental research Good written