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predictive checking, model comparison) • Computational modelling with Python and Dynesty, JAX, NumPyro, and PyTorch • Use of asteroseismic and spectroscopic survey data (e.g. PLATO, Gaia, APOGEE, TESS) • High
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candidate with a strong quantitative background (e.g., in computer science, statistics, bioinformatics). The following skills are essential for this project: Excellent programming skills in Python. Proven
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computing paradigms (e.g., MPI, CUDA, etc.); designing and managing new electromagnetic solvers and associated codebases in C++ and/or Python. This is a particularly good opportunity for students who
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/Simulink/Python for modelling, simulation, and control design. Experience with genset systems, hybrid powertrains, or real-time control applications is highly desirable. A practical interest in system