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Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, or JAX Experience with HPC and GPU-accelerated computing Familiarity with foundation models / LLMs; interest in reproducible
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10%-30%, Zurich, fixed-term The Atmospheric Physics group at the Institute for Atmospheric and Climate Science (IAC), ETH Zurich, has an opening for a Student Research Assistant. We are seeking a
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of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a significant computational component in deploying multi-GPU codes
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megawatts. To transfer energy efficiently from the grid to CPUs/GPUs, higher system voltages are required in data centres/computer racks, and efficient power electronics converter systems based on SSTs
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plasma physics (XGC, IPPL). Expected qualifications: A Master's degree in Computer Science or Applied Mathematics. Necessary knowledge: Modern C++, GPU computing with CUDA/SYCL, MPI, Krylov solvers