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to join the AI for Genome Interpretation (AI4GI) group at the IGMM (CNRS, Montpellier). The project is a collaboration between IGMM and IMAG, at the interface of genetics, bioinformatics, statistics
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
-Negative Matrix Factorization will be explored. The second challenge is to leverage the derived statistical models to design automated data-driven procedures for the estimation of epidemiological indicators
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of current methods to detect balancing selection resulting from other mechanisms than HA, such as NFDS and FS using simulations. He/She will further explore new combinations of statistics, relying notably
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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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skills and/or experience desired: • in at least one, and preferably two, of the following areas: applied mathematics, particularly in nonlinear PDEs, theoretical physics (statistical physics and/or
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Job related to staff position within a Research Infrastructure? No Offer Description Development of theoretical models of cell migration with memory Modeling in statistical physics and soft matter
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that incorporate horizontal transfers, and to use these models to obtain statistical estimates of the main evolutionary dynamics of TE families across species (for example, horizontal transfer and extinction rates
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microbiota research would be highly appreciated. Knowledge of immunology or neuroinflammation will be valuable. Character traits and work ethic: Scientific rigour in the design of experiments and statistical
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communities to environmental stresses and the cascading effects on ecosystem functioning. - Setting up experiments - Ecophysiological measurements in the laboratory - Statistical analysis of collected data
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postdoctoral researcher will investigate how data fusion techniques can be incorporated into FORMOSA to address the challenges described above. They will propose new methodologies based on statistical inference