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Leveraging the spatio-temporal coherence of distributed fiber optic sensing data with Machine Learning methods on Riemannian manifolds Apply by sending an email directly to the supervisor
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of programming, learning theory, parallel algorithms or quantum computing Research publications in theoretical computer science conferences and journals Experience in teaching Computer Science topics
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Nature Careers | Port Saint Louis du Rhone, Provence Alpes Cote d Azur | France | about 2 months ago
protein expression and purification, capable of producing thousands of proteins in parallel within weeks . 2) Eukaryotic expression systems facility for production of challenging protein targets. 3) A fully
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, dynamic and innovative researcher to integrate our community. The ideal candidate will possess deep expertise in the application of cutting edge computational methods to understand the brain mechanisms
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must have advanced training in fundamental physics and/or scientific computing, with an ability to handle massively parallel simulation codes and to contribute to their development. Experience with
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Research Engineer in optimization and Design Space Exploration for Next-Generation Computing Systems H/F IN SUMMARY, WHAT DO WE OFFER YOU? We are looking for an Research Engineer in optimization and
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the exact calculation of the square-root and inverse square-root of the source distribution covariance matrix. This approach offers analytical and computational advantages in comparison to existing methods
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on several aspects to explore in parallel: - Develop the experimental set-up to enable Low-Energy SAXS measurements on Attolab’s set-up (through punctual mission (2 or 3 times a year for 1 to 2 weeks
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degree in computer science and: You have a good knowledge of C++ You have skills in software engineering. You are familiar with common development environments and associated tools Knowledge of parallel
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learning, focusing on identifying abrupt shifts in the properties of data over time. These shifts, commonly referred to as change-points, indicate transitions in the underlying distribution or dynamics of a