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associated with the implementation of new systems may generate environmental or social conflicts. Expected contributions of the Thesis The aim of this project is to develop and validate a model to help
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foundations in waveform design and advanced signal processing. In particular, energy-efficient precoding algorithms have been developed for distributed MIMO systems and are currently validated through numerical
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-off between algorithmic complexity and conservatism by finding a balance between the two strategies described above. The interest and limitations of this idea will be illustrated in particular by a
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the development of efficient algorithms and codes for multilinear algebra, with a particular focus on the use of innovative parallel programming models and tools. In the context of this task and as part of the Exa
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la stabilité des algorithmes et à l'efficacité computationnelle. Une partie de la thèse sera également consacrée à des travaux expérimentaux visant à caractériser le comportement mécanique de systèmes
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3D environments. • Design of a robust control architecture to ensure autonomous navigation using information from the optical localization system (development of estimation algorithms, use of observers
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Les estimateurs sécurisés sont des algorithmes qui exploitent la
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
to advancing algorithms for human-centered robots: robots that are not working autonomously in isolation, but that instead react, interact, collaborate, and assist humans. To do so, these robots need
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Prof. Marc-Emmanuel Dumas in Lille, France. The successful applicant will develop high-throughput high-resolution mass-spectrometry based metabolomic workflows (automatization of sample preparation
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laboratory, and of the Computer Science Department of IMT Atlantique. The RAMBO team is studying how ambient devices and robots can develop increasingly complex skills based on active learning, artificial