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to identify dysbiosis signatures. Apply bioinformatics tools for microbiome data analysis (ex, QIIME2, MetaPhlAn, Kraken2). Collaborate on multi-omics data integration and analysis. Contribute to manuscript
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PhD students and research assistants involved in the project. Provide training on experimental techniques, data analysis, and scientific writing. Requirements: Educational background: A Ph.D. in Plant
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factors, and mobile elements in microbiome datasets. Collaborate with clinical partners and microbiome researchers to integrate multi-omics data for comprehensive resistome analysis. Publish high-quality
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in UM6P's collective projects and external missions, and to provide support to students (PhD and Master's), i.e., supervision for the writing of reports, dissertations, and end-of-study papers. Skills
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of degraded technosols. Our approach is integrative, combining the analysis of plant diversity, functional traits, soil quality, biotic interactions, and ecophysiological properties. Responsibilities: Supervise
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analysis (ex, QIIME2, MetaPhlAn, Kraken2). Collaborate on multi-omics data integration and analysis. Contribute to manuscript writing, conference presentations, and grant applications. Required
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, especially in the area of simulations. Criteria of the candidate: PhD in the field of Computational Biology, or related fields Strong publication record in leading international journals Excellent background
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of biology and the effect of mutations. He/she would also be required to have a sound computational background, especially in the area of simulations. Criteria of the candidate: PhD in the field
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a postdoctoral candidate in the area of federated learning and wireless communications. The candidate must hold (or about to complete) a PhD in the related fields. The candidate will be involved in a
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partners and microbiome researchers to integrate multi-omics data for comprehensive resistome analysis. Publish high-quality research articles and present findings at international conferences. Contribute