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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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Computer Science, Applied Mathematics, Physics, Computational Biology, Neuroscience with Computational or Theoretical focus, or a closely related field. Preferred Qualifications: Familiar with Information Theory
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, Information Technology, Applied Mathematics, Physics, Chemistry or related field. Familiarity with Mathematica and/or MatLab. Experience with Linux file systems, such as XFS, ZFS, RAID etc. Skilled with RedHat Linux
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, Information Technology, Applied Mathematics, Physics, Chemistry or related field. Familiarity with Mathematica and/or MatLab. Experience with Linux file systems, such as XFS, ZFS, RAID etc. Skilled with RedHat Linux
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] Subject Areas: Applied Mathematics, numerical methods, simulation and modelling Appl Deadline: 2025/05/31 11:59PM (accepting applications posted 2025/02/13) Position Description: Position Description
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, electrical engineering, biomedical engineering, physics or applied mathematics. You should present with expertise in advanced signal and data processing and its applications to cutting-edge imaging. Developing
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a challenging problem. Candidate profile PhD on optimization and/or image processing. Strong background in applied mathematics, image processing, learning methods and algorithms. Good coding skills
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on applied mathematics, software development, low-level computer science/computer engineering, and/or operations research. (3) The design, use, and testing of electromagnetic materials; development and use
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. First, efficient and scalable training procedure are still needed, irrespective of whether the training is done off-line on a traditional GPU-based architecture, on neuromorphic hardware. Second
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. Qualifications Required Qualifications: Ph.D. degree in engineering, mathematics, physics, or computer science. Successful publication records in thermos-fluids area. Expertise in model development using lattice