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skills (one or more of the following strongly desired) Exploratory analysis of massive datasets (machine learning methods) Spatial data analysis and Geographic Information Systems (GIS) Forecasting and
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Skills/Qualifications Strong background in Operating Systems and Linux development Knowledge of memory management mechanisms and system-level programming Experience with Machine Learning models (design
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. This postdoc will be conducted within the ANR-funded ITS-STORY project, a multidisciplinary collaboration involving computer scientists, historians, ergonomists, the Mémorial de l'Internement et de la
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 29 days ago
Research Framework Programme? Horizon Europe - ERC Reference Number 2025-09382 Is the Job related to staff position within a Research Infrastructure? No Offer Description We propose a two-years postdoc
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. - Knowledge in programming, data treatment, electron diffraction simulations, mathematical skills, knowledge about machine learning and artificial intelligence is a plus. Website for additional job details
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 1 month ago
, CIRAD AMAP, CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica). This is a postdoctoral position in Machine Learning, more
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in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in
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research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
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Inria, the French national research institute for the digital sciences | Bures sur Yvette, le de France | France | about 2 months ago
mathematical modeling (preferably physiological systems) and/or control theory. -Experience in signal processing and artificial intelligence methods (time-series analysis, machine learning, multimodal
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visualization. Experience with GWAS, Bayesian modelling, and/or machine learning applied to biological data. Strong programming skills (R, Python) and ability to manage large-scale -omics datasets. Good