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-using models, retrieval systems, or related AI systems Experience with large-scale datasets, distributed training, or high-performance computing environments Interest in scientific applications of AI
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, scientific computing, and emerging AI. The project tasks will include resource-aware training methods and hardware implementation, including the design, implementation, and verification of KAN accelerator
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on model development, robustness, and long-term reliability. You’ll have access to Susquehanna’s extensive proprietary datasets and large-scale computing infrastructure—including a rapidly growing
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Computational Science and Engineering Laboratory at Harvard University invites applications for postdoctoral position at the interface of scientific Computing and Artificial Intelligence for
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Job Description Do you want to advance high-performance computing? Join the Embedded Systems Engineering section at DTU Compute and develop research on programming models, compilers, operating
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, focused on computational astrophysics (CCA), biology (CCB), mathematics (CCM), neuroscience (CCN) and quantum physics (CCQ), as well as a scientific computing core (SCC) that maintains state-of-the-art
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PhD Student in Pervasive and Mobile Computing Skelleftea Reference number 4702-2026 Are you ready to take the next step in your academic journey? As a doctoral student with us, you will work closely
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geometry, number theory, data. * Qin Li: Scientific computing, machine learning, inverse problems. * Hanbaek Lyu: Combinatorics, probability, optimization, and machine learning. * Laurentiu Maxim
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developing research code in Python and working with large datasets; experience with C++, scientific computing, or high-performance computing is a plus * Excellent problem-solving skills and an interest
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and working with large datasets; experience with C++, scientific computing, or high-performance computing is a plus * Excellent problem-solving skills and an interest in using quantitative models to