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. - Applied Mathematics and Statistics: Knowledge of statistical methods and algorithms for data analysis, including model fitting, regression, and sensitivity analysis. Expertise - Scientific Collaboration
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to medium level skills in programming, image analysis and electronics • Solid knowledge and hands-on experience in light and electron microscopy. • Solid formation in genetics, statistics and molecular
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, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
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hold a PhD in the fields of ecology or evolutionary biology, or biostatistics/biomathematics. Required skills: - Data analysis using R and database management - Statistical modelling for ecology
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, statistical analysis and visualization of genomic and phenotypic data. * Interpretation of experimental and bioinformatic results in the context of bacterial adaptation to stress. * Contribution
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- Good communication of scientific results -Knowledge on evolution, statistics, evolutionary genomics, especially for sex chromosome studies (phylogenomics, orthology, selection, synteny, SNPs, structural
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(statistics, bioinformatics) to identify correlations between siderophore production, microbiota composition, and colonization resistance. - Present results clearly and rigorously (team meetings, reports
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking