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- MOHAMMED VI POLYTECHNIC UNIVERSITY
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computational tensor network techniques as well as background in quantum information science defined broadly is viewed favorably. Information about Prof. Maghrebi’s research group can be found at: https
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: - Quantum computing with qudits, quantum error correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de
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algorithms, error correction, or many-body quantum systems. o Proficiency in numerical simulations (e.g., tensor networks, quantum circuit modeling). · For Experimentalists: o PhD in atomic/molecular/optical
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. Experience in phase-contrast and/or dark-field x-ray imaging. Experience in working with photon-counting x-ray detectors Experience with scanning x-ray imaging such as SAXS mapping, SAXS tensor tomography
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functional data analysis, tensor regression, high-dimensional variable selection, longitudinal and survival analysis, machine/deep learning, bioinformatics methods in -omics data are preferred. Demonstrated
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learning and tensor libraries such as PyTorch We Are Delivering Scientific Excellence Los Alamos National Laboratory is more than a place to work. It is a catalyst for discovery, innovation and achievement
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Science and Quantum Computation Tensor Learning Team , Generic Technology Research Group, RIKEN Center for Advanced Intelligence Project (Team Leader: Qibin Zhao) Functional Analytic Learning Team
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Mathematical Physics in the last 40 years. Researchers in this area will be expected to have knowledge of the aspects of Quantum Groups associated to Representation Theory, Tensor Categories, Poisson Geometry
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with tensor networks, AI in physics and materials, etc.). A Ph.D. in Physics or a closely related field is required. The initial appointment will be for one year, and is renewable for another one or two
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Ph.D. in Physics or a closely related field is required. Candidates with a strong background in quantum many-body theory and experiences in quantum Monte Carlo and tensor network methods are encouraged