41 machine-learning-"https:" "https:" "https:" "https:" "https:" Postdoctoral research jobs in France
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- CNRS
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silico identification of candidate developmental pathways explaining tradeoff variation. Contribute to advanced statistical analyses and interpretable machine learning approaches (in collaboration with
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University of Savoie Mont Blanc (USMB) that brings together expertise in machine learning and information fusion, as well as networks and systems. It develops methods for processing and managing data in
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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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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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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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. This recruitment is funded as part of the implementation of a Prematuration Programme by the Alliance Sorbonne Université University Innovation Cluster (PUI-ASU). Where to apply Website https://utc.recruitee.com/o
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
the machine learning community as challenging, high-dimensional testbeds. Notably, the recently developed WOFOSTGym simulator \cite{solow2025wofostgym}, bridging crop modeling and RL, received the Outstanding
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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on the plants Arabidopsis thaliana will generate maps of depolarization, retardance, dichroism, and optical axis azimuth, which will feed machine learning models developed by the project partners to identify
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difficult to couple with basin simulators. Geochemical metamodels, particularly those based on machine learning, can significantly reduce computation times while maintaining physico-chemical consistency