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open-source software packages and set up computational pipelines. As a bio-informatics research lab, we publish software packages in Python and R for specific, cutting-edge analysis of large-scale
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-on experimental support to researchers across the lab, assisting with study design, sample preparation, acquisition, analysis, and data visualization Oversee tissue processing workflows, including isolation
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bring science to life. Main responsibilities: Content creation You translate scientific content into accessible and attractive visuals, videos, reels, and social content. This includes creating strong
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-edge technologies for next generation sequencing. Our user base consists of both VIB and non-VIB scientists throughout Europe. Key applications are gene expression analysis, whole genome sequencing
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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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and propose meaningful and testable hypotheses, grounded in disease biology. Perform end‑to‑end processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g
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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell
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; support multi‑omics data integration and analysis across multiple research groups; and collaborate on the development and maintenance of computational pipelines for spatially resolved transcriptomics and
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Maintaining consumables stocks necessary for the above two activities Basic maintenance of peptide synthesizer, LCMS and HPLC Biophysical analysis of proteins Documentation of experimental
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Biology (VIB.AI), more specifically in the Ghent branch of VIB.AI. Profile text Academic education You contribute to various lecturers in the discipline of bioinformatics, data analysis of large-scale (bio