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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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: · 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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, with expertise both in theoretical methods and in numerical study, and with a particular focus on the application of quantum information driven tools, such as tensor networks or convex relaxations
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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
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of research include quantum Monte Carlo methods, density matrix renormalization group and tensor network states, and artificial intelligence and neural networks, with particular focus on applying
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methods tailored for different types of multivariate data, such as time series, spatial data, spatio-temporal data, functional data or tensor-valued observations. The work of the postdoctoral researcher
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for different types of multivariate data, such as time series, spatial data, spatio-temporal data, functional data or tensor-valued observations. The work of the postdoctoral researcher will focus on developing
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quantum-classical approaches for many-body simulations Tensor network and entanglement-based methods in many-body physics Qualifications A Ph.D. in theoretical nuclear physics, quantum information science
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in time series, tensor data analysis, and related topics. Duties include identifying important problems and novel approaches related to analysis of tensor and other complex time series and related
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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