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to, flow cytometry, ELISA, RT-PCR, bulk and single cell RNA sequencing, imaging and other emerging technologies (e.g. imaging mass cytometry, spatial transcriptomics, metabolomics/proteomics) – including
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involving tissue microarrays. F2 Technical experience in aspects of spatial biology, such as multiplex phenotyping, next generation sequencing methodologies, spatial transcriptomic analysis. F3 Data analysis
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omics data analysis. Research experience in systems biology, computational biology or related field. Experience with omics data analysis (e.g. transcriptomics, metabolomics). Knowledge of machine learning
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modalities in the rodent brain (3D light-sheet microscopy, spatial transcriptomics and MRI of the same brain) to learn MRI contrasts that can depict neuronal and glial cell density and morphology. You will
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Contribute to the analysis of single-cell RNA-seq, spatial transcriptomics, and multi-omic datasets Apply computational and machine learning approaches to build mechanistic biological models and rationally
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including sc/snRNA and spatial transcriptomics, patient-derived models, systems biology and AI platforms Opportunity to obtain a PhD within the U Strasbourg MD-PhD program Tenure track program at Inserm and U
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flow cytometry, cell sorting, mouse models, molecular biology techniques, and immune profiling assays. · Analyze and interpret complex datasets, including genomic, transcriptomic, and
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models to evaluate therapeutic efficacy and pharmacokinetic profiles. Gaining exposure to cutting-edge transcriptomic, proteomic, and "imageomic" (high-content image informatics) datasets, as
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We are seeking to appoint a Research Associate in computational genomics and long-read transcriptomics to join the Gustavsson Group at the UK Dementia Research Institute at the University of
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, molecular and transcriptomic analyses, laser-capture microdissection, and the generation and characterization of lipid nanoparticles. You will work in an interdisciplinary environment combining expertise in