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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 21 hours ago
to develop Computer Vision algorithm and Interfaces for collaborations with Historians teams. Specifically, the research will focus on structured data with clear repeated patterns, such as characters in a text
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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creation of a database for the various pollution sensors with a view to training online (non-embedded) models in the first instance. - Development of a machine learning algorithm based on the study database
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 19 days ago
distributed optimization with noisy communication channels, accurately study the selected algorithms, participate in the development and maintenance of the PEPit (https://pepit.readthedocs.io/ ) software
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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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influence helps detect labeling errors or prioritize unlabeled images, optimizing the learning algorithm and service quality. The doctoral student will carry out their work at IMAG (UMR of Mathematics) and
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strong background in scientific computing to contribute to various algorithmic patterns in an agile development environment. Within an Agile team set up: - You will contribute according to your expertise
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using wall oscillations, relating small-scale turbulence to heat transport, modelling large-scale outer flow effects, and developing low-order heat transfer models. Partnerships with industry will
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park, in a dynamic ecosystem that brings together academics and companies of all sizes. The Signal team of the i3S Laboratory (https://i3s.univ-cotedazur.fr/signal ), aims to develop advanced, innovative
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of the Khovanov–Seidel representation in new cases, using Garside-type approaches. Developing extensions of Garside theory to the case of infinitely many atoms may also be of interest and will rely on the study of