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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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and statistical analyses, and scientific English will be appreciated. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR6049-JEAFOL-001/Default.aspx Work Location(s) Number
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: Data analysis - activities: data analysis, statistical analysis, spatial datawet analysis Where to apply E-mail Crystele.leauthaud@cirad.fr Requirements Research FieldAgricultural sciencesEducation
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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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evolutionary mechanisms: for example, heterozygote advantage (HA), negative-frequency dependent selection (NFDS) or spatially/temporally fluctuating selection (FS). Recently, new research showing that balancing
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24 Oct 2025 Job Information Organisation/Company CNRS Department Laboratoire d'océanographie physique et spatiale Research Field Physics Researcher Profile First Stage Researcher (R1) Country France
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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