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Background in high-performance computing (HPC) or cloud environments Comfortable working in Linux/Unix environments Advantageous qualifications: Development of parallel applications Strong Python knowledge
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experience in developing software for scientific applications, data analysis, or real-time systems is desirable. Experience with parallel computing and optimization techniques for handling large datasets
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. Scientific IT Services (SIS - a section with ITS) aims at bridging the gap between computational research and IT services and infrastructure provisioning. We are working closely together with ETH researchers
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plasma. The main methods used are computer simulations for studying dust dynamics and analysing in situ measurements by spacecraft that carry a dust detector on board. We collaborate with researchers in
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, continuous integration). Adapt software for parallel computing, optimization workflows, and high-performance computing environments. Contribute to software deployment, testing, and benchmarking across multiple