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biology, genetics, single-cell and spatial transcriptomics, advanced imaging, and bioinformatics. The main objective will be to identify the gene networks involved in muscle morphogenesis, reconstruct
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bioinformatics, particularly single‑cell RNA‑seq, multi‑omics, and spatial transcriptomics analysis. Specific Requirements Proficiency in Python and R; familiarity with common bioinformatics tools and pipelines
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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biology, bioinformatics, infectious-disease epidemiology, evolutionary or ecological biology, or a closely related field. Strong programming skills (R, Python, and/or other) Familiarity with version control
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Bioinformatics analyses guided by prior mechanistic knowledge will be conducted, using the known grouping structures among features in the omics data and dedicated approaches for structured data analysis With
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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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computing; data science; signal processing; neuroengineering; bioinformatics; computational neuroscience. A PhD is not required. Candidates holding a PhD are also eligible, provided that their profile
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these processes requires AI and bioinformatics methods able to integrate heterogeneous, high-dimensional data. The ShadowEV-GBM project brings together spatial omics, metabolomics/lipidomics, molecular profiling
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bioinformatics tools enabling the integration of multi-scale information and a better understanding of the underlying mechanisms. The expected results will contribute to a better understanding of the functional
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French National Institute for Health Research (INSERM) | Paris 15, le de France | France | 2 months ago
to vaccination. The approaches developed will combine molecular biology, omics analyses, and bioinformatics, using both experimental models and clinical samples. This chair fully aligns with INSERM’s strategic