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the emergence of edge computing, data storage will become more geo-distributed to account for performance or regulatory constraints. One challenge is to maintain an up-to-date view of available content in such a
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the ability of neural networks to learn unknown posterior distributions distributions. Their use in the field of image microscopy, however, remains limited. The purpose of this PhD thesis is to develop
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fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
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PhD degree in Computer Science, Physics or a related field Experience with parallel programming models Strong programming skills in C/C++ and/or Python Knowledge of distributed memory programming with
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domain. Work in computer networks and computers. Cloud computing drastically changed how software is developed and deployed. Nowadays cloud applications are designed as distributed systems continuously
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Additional Information Eligibility criteria - a PhD in computer science - sound knowledge of energy metrics in distributed systems - knowledge of performance evaluation in Cloud environments - knowledge
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NeuroSchool, Aix-Marseille Université | Marseille, Provence Alpes Cote d Azur | France | 3 months ago
and for international co-supervised PhDs. This project is one of the proposed projects. Not all proposed projects will be funded, check our website for details. State of the Art Social interactions
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Virtual laboratory to predict the ability of a fluctuating biomass to satisfy a material use-VARIOUS
and organic waste) of which the properties are different and subject to seasonal and climatic variations. For the bioeconomy, it is therefore necessary to sort biomass sources according to the target
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arrival. By joining our team, you'll have the opportunity to contribute to the future of real-time verification, making a meaningful difference in the world of distributed systems. If you're passionate