193 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:"-"ICTS-TIFR" positions at ETH Zurich in Switzerland
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-phonon coupling elements. With these, dedicated scattering rates can be computed and then used in quantum transport simulations. Down the line, we aim to pre-train a common GNN backbone model capable
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the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
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The Quantum AI lab at ETH (Prof. Juan Carrasquilla ) invites applications for postdoctoral positions to work at the intersection of computational quantum many-body physics, automated scientific
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the international team of the Ultrafast Spectroscopy and Attosecond Science group. Gain access to a wide range of experimental and analytical facilities, including high-performance computing resources, and
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, performance analysis, system architecture, distributed applications at scale, etc. Applicants should be strongly rooted in computer science, have internationally recognized expertise in their field, and pursue
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executing computational projects. Prior experience with DFT-based electronic structure calculations or other computational quantum-mechanical many-body techniques. Programming skills in either Python, Fortran
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is an advantage Familiarity with Linux-based computing environments; experience with high-performance computing (HPC) systems is an advantage Knowledge of reproducible research practices, including
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100%, Zurich, fixed-term We invite applications for a PhD position in the field of quantum computing, to be advised by Dominik Hangleiter and co-advised by Renato Renner. In our group in Zurich
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optimising high-power, medium-frequency transformers (MFTs). Compact, highly efficient transformers that operate at kilohertz frequencies are key components of high-power DC-DC converters, which are the core
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, optimized for high-performance computing (HPC) environments Classifying ice crystal habits using Convolutional Neural Networks (CNNs) Providing intuitive graphical interfaces for user interaction and data