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; while they are trained using GPU-based optimization methods, the actual information processing takes place without a GPU, making them energy-efficient and fast. Diffractive networks are to be designed
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Biotech Research and Innovation Centre, The Lund Group, University of Copenhagen | Denmark | about 1 month ago
collaborators. We believe that cooperation and collegiality are essential elements for research successes. You can find more information about the team and our work here: https://www.bric.ku.dk/research-groups
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principles and research data management. Experience with high-performance computing, cloud computing, GPU acceleration, or distributed data processing. Experience participating in international scientific
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jet physics, heavy-ion collisions, and detector performance studies. Experience in scientific machine learning, deep learning, foundation models, or multimodal AI. Experience with GPU programming
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
, QUDA , Grid) and GPU computing. Experience with statistical analysis of large Monte Carlo datasets, including inverse-problem and Bayesian methods. Experience using DOE computing allocations ( NERSC
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with high-performance computing, GPU programming, parallel programming, cloud computing, and/or related methods including running numerical simulations of complex workflows. Demonstrated technical
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to start imminently, and before mid October this year. The project intended for the post-doc is part of a collaboration within my group on the Google Willow Chip project (https://www.bbc.co.uk/news
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impact on sustainability and future technologies. For more information: https://saragovi.science/ Being a doctoral student As a doctoral student, you are both admitted as a student and employed at Lund
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workflow tools such as Nextflow or Snakemake, version control such as Git, and reproducible computational environments is preferred. Familiarity with GPU-accelerated genomics, high-performance computing