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Master’s theses Requirements: Master’s or PhD degree with above-average results in Applied Maths (analysis, numerics, modeling) or in a comparable program with a strong math. focus and knowledge in
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managing supercomputer resources Strong skills in algorithm development for large sparse matrices Excellency in programming GPU accelerators from all major vendors Very good command of written and spoken
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-end GPUs We will jointly choose tasks based on your expertise and interests. Most important is a strong interest in scientific methods, a solid knowledge foundation (e.g. studying computer science, open
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training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and familiarity with machine learning
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for the position the following: A Ph.D. in the field of Applied Mathematics, Computer Science, Computational Science and Engineering, or similar. Knowledge of numerics as part of a degree program. In particular