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19 Sep 2026 Job Information Organisation/Company CNRS Department Propagation des Ondes : Etude Mathématique et Simulation Research Field Engineering Physics » Acoustics Engineering » Materials
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-VIS-NIR). Experience in hyperspectral data processing (HMSPL, μXRF, μXAS) and statistical analysis (clustering, machine learning) is preferred. Familiarity with fossilization processes and taphonomic
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present scientific results. # Software and tools - Proficiency in standard computer tools. - Experience with mass spectrometry data processing and analysis software. # Personal skills - Autonomy, rigor, and
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(LORIA) in Nancy (France).analysis. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7503-MARMIN-003/Default.aspx Requirements Research FieldMathematicsEducation LevelPhD or equivalent Research
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Principal Investigator of the OrDOTime project, and a collaborator on the project. Literature review, design of behavioural experiments, data collection, data analysis, writing scientific articles
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; - strong data analysis and interpretation skills; - the ability to work effectively in a multidisciplinary team environment; - good scientific communication skills; - strong scientific writing skills in
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. Identification and analysis of dissolution, passivation, and interfacial reaction mechanisms at material/electrolyte interfaces. Use of scientific programming tools for data analysis and visualization (Python
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. The successful candidate will also participate in data analysis, dissemination of research results through scientific publications and conferences, and technology transfer activities. Design and fabricate three
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) analysis of thermal events, subsidence, as well as modelling and production of H₂ in high-temperature contexts (WP2); 3) development of 3D sedimentary basin models integrating these data, and restore
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
this context, the offer is about continual audiovisual robot perception, and aims to develop methods and algorithms to continuously extract cues about human behaviour from audio and visual data in real-world