129 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" positions in France
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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving
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active materials by making use of artificial molecular machines. SPRING will establish innovative concepts to elaborate (i) active (supra)molecular systems, (ii) new synthetic objects to study some
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self-adaptation capabilities. Three major challenges have been identified: (P1) modelling uncertain environments where robust, weakly supervised machine learning algorithms can be deployed to irrigate
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for highly motivated candidates currently enrolled in a Master’s degree or engineering program in applied mathematics or computer science. Candidates should have a solid background in machine learning and be
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at least two of the following areas: Machine learning and associated mathematical foundations Embedded systems Analog/mixed design [1] https://emergences.pepr-ia.fr [2] https://www.frontiersin.org/articles
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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researchers with ample experience in MEG/EEG data analysis, BCIs, signal processing, deep learning for brain imaging analysis, biomedical statistics, dynamical systems and research on motor control. The lab has
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assimilation, and at least a practical understanding of machine learning. Both profiles should bring a curiosity for bridging disciplines and a drive to innovate at the intersection of AI and ocean science
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of sea turtles - Developing innovative machine learning methods to analyze the sounds associated with these behaviors - Automating the processing of audio and visual data to optimize the quantity and
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 27 days ago
hyperscanning neuroimaging data, using advanced statistics and machine learning methodologies for temporally-sensitive data, such as GLMM, Random Forests, LSTM, etc.. Use of MatLab for pre-processing, and