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metazoans by combining deep learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability
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procedures - Managing the experimental implementation of bulk RNA-seq and single-cell RNA-seq protocols - Analysing bulk RNA-seq and single-cell RNA-seq data using bioinformatics - Corroborating bulk
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siderophore production. - Process and analyze experimental data (statistics, bioinformatics) to identify correlations between siderophore production, microbiota composition, and colonization resistance
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the MuSST code (Multi-Scale Simulation of Tribology https://tribo-pprime.github.io/MUSST/ ), which enables multi-scale simulation of flows between rough surfaces. TASK description
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partnerships, sensitive data or the strategic interests of the organisations involved, particularly as this thesis is confidential. We are seeking a highly motivated candidate to be involved in a
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, from the design and implementation of the experiments to data analysis and dissemination of the findings. The main responsibilities will include: • Designing and implementing experimental paradigms
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assemblages to define biozones. Build age-depth models incorporating uncertainties, sedimentary hiatuses and reservoir effects. Combine chronological, stratigraphic and biological data to develop
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- Complete structural characterization of nanoparticles by TEM (HRTEM, STEM-EDX, STEM-HAADF, STEM-EELS) - Literature review - Data analysis - Publication of articles and report writing CEMES is a
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, transcriptomic and imaging data and contribute to publications and scientific presentations. The position is based at the Institut de Biologie Paris-Seine (IBPS), Sorbonne University / CNRS / INSERM, within
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work in close collaboration with the consortium partners, including the teams of Dr. Lucie Brisson (Bordeaux) and Prof. Sébastien Lecommandoux (Bordeaux). Where to apply Website https