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to the development of bioinformatics pipelines implementing new and traditional methods. Participate in complementary activities of the research group. The position is linked to the Department of Genetics
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, RT-PCR). Data and Bioinformatics: Genomic and transcriptomic analysis. Comparative genomics of pathogens and hosts. Phylogenetic analysis and sequence databases. Statistical analysis of biological
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structural bioinformatics, machine learning, and high-performance computing, we will build the first Human Proteome-Wide Frustration Atlas — a resource to better classify genetic Single Nucleotide Variants
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bioinformatics such as Python, R, EdgeR, Cytoscape, ggtree, etc., as well as courses in data visualization and web development will be considered. At least 2 publications as first author and more than half a dozen
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. Tasks: Estimate genetic correlations, polygenic risk scores, prediction of causal genes, prediction of differential expression in brain, and construction of gene networks. Bioinformatic analyses will be
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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and
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GHG emissions. Lab measurements of soil C and soil aggregates and microbial community assessment, including bioinformatics. To perform literature review, data collection and management, involving
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bioinformatics. To perform literature review, data collection and management, involving statistical analysis including multivariate statititical methods. To write scientific articles and results dissemination in
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techniques (qRT-PCR, ddPCR, NGS, WB, IHC, IF, cytometry). Analysis of -omics data using bioinformatics tools, preparation of presentations of results and writing of articles. Candidates should have the ability
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about new technologies and programming. Bioinformatics, Biosystems engineering, Data Science, Mathematics, Statistics, Computer Vision or related fields. In this case, candidates must demonstrate