148 parallel-and-distributed-computing-phd-"Multiple" positions at ETH Zurich in Switzerland
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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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of SIS (e.g., HPC systems engineers, data scientists, research software developers) and external collaborators. Profile a PhD or equivalent in Computational or Computer Science, Engineering, Physics, or a
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research on power electronic converter systems, which are required, for example, in future energy distribution systems for the integration of renewable energy sources or in traction applications/electric
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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
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with the Control and Automation group at inspire AG. The project is part of a large group effort involving ETH, inspire AG, and ZHAW and brings in multiple engineers and PhD students to continuously
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100%, Zurich, fixed-term The Sensing, Interaction & Perception Lab invites applications for a PhD position in Computational Interaction, focusing on sensor-based input detection for Augmented and
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-transportation system, we are looking for a: PhD Student in Data-Driven Policy Optimization for Transportation and Energy (100%) Project background Our energy and transportation systems are rapidly transforming in
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develop and apply computational approaches to identify policy strategies that are politically feasible and compatible with changing land-use demands, while also considering the distributional impacts
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technologies promise to revolutionize multiple branches of science by solving problems that cannot be tackled by classical systems. While efficient and large-scale quantum computers are still far from being