186 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ" positions at ETH Zurich
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to work at the interface of quantum optics, quantum information science and quantum many-body physics. Led by Prof. Wenchao Xu , the EQE group develops programmable quantum systems based on neutral atoms
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optimization is necessary for lower optical losses, increased component performance, and improved interfacing with optical fibers. The advertised position will work on two main projects: (1) TFLN circuit
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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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-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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have enabled unprecedented control over light-matter interactions, catalyzing breakthroughs in imaging, nonlinear optics, and photonic computing. We leverage these developments to advance the field
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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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of interferometric optical systems Perform straylight and ghost analysis to ensure compliance with high-contrast performance requirements Contribute to the development of beam combination and wavefront control
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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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links to the ETH AI Center and the Reliability and Risk Engineering Lab . Job description Collaborate with other researchers to develop high-fidelity emulators for large-scale, energy system optimization