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complexity of relationships between the nodes of networks with a mul-tidimensional nature, tensors are used to represent these kind of networks. For example, the transport network mentioned earlier would be
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physics is especially interesting due to the presence of exotic excitations, potentially non-Abelian. The TensQHE project aims to develop modern numerical tools based on tensor networks, within an open
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of relationships between the nodes of networks with a mul-tidimensional nature, tensors are used to represent these kind of networks. For example, the transport network mentioned earlier would be represented by a
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, theoretically grounded, and explainable. The research sits at the crossroads of quantum information science, tensor network theory, and generative modeling (transformers, diffusion models, etc.). Key research
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 4 hours ago
capabilities to produce and polarize the solid targets needed for this program. In the near term, our group will focus on the Jefferson Lab Azz and b1 experiments, which will probe tensor po- larized deuterons
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-based electronic structure methods, quantum Monte Carlo, tensor networks, or quantum embedding methods, etc. -ML-augmented numerical method development. -High-performance computing (HPC). Certifications
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field is required by the starting date of the position. Experience in one or more of the following areas is especially desirable: non-Lorentzian symmetries, holography, higher-spin theory, tensor gauge
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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: · MATLAB · Python · ROS · Computer vision and/or YOLO · Pytorch and/or Tensor Flow · LiDAR · GIS · GNSS receivers Minimum Qualifications: Doctoral degree in Mechanical Engineering, Electrical Engineering, or
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed