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at the intersection of numerical linear algebra and advanced HPC. The candidate will join an international environment, with opportunities to collaborate with experts from the USA, and KAUST and publish in top-tier
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to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non fully observed data. These methods can be applied to complete or predict links in a network. However
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computing (HPC). This position offers an exciting opportunity to work on cutting-edge research projects at the intersection of numerical linear algebra and advanced HPC. The candidate will join an
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challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non