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Research Framework Programme? Not funded by a EU programme Reference Number PID2023-152793NA-I00 Is the Job related to staff position within a Research Infrastructure? No Offer Description Job description
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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positions in High-performance computation and machine learning, Chemical Physics, Physical Chemistry, Nano-science, Biophysics, Statistical Physics and Complex Systems. The positions are normally for one year
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, Nonlinear and Complex Systems , quantum information/computation , Quantum Simulation , Statistical physics Appl Deadline: 2025/06/30 11:59PM (posted 2024/08/15) Position Description: Apply Position
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This position will focus on the molecular beam epitaxy (MBE) growth and characterization of thin films and heterostructures of complex oxides. The successful candidate will also engage in the micro- and nano
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faculty, and conducts a wide range of collaborative quantum research in the areas of quantum computing, quantum algorithms and complexity, quantum cryptography, quantum program verification, quantum machine
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. Translates complex computational results into biologically meaningful insights in collaboration with wet-lab teams. Maintains thorough documentation of analyses, pipelines, and datasets in version-controlled
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Are you passionate about applying quantum computing to addressing real-world challenges? Join us to develop quantum optimization methods that support the transition to sustainable and resilient
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Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job ID: ESI128PD225 The Erich Schmid Institute of Materials