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(linking phenotypes, imaging, cytometry, or other readouts to transcriptomics) Statistics / machine learning for biological inference (model validation, differential state testing, embeddings/classifiers
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. Demonstrated experience in machine learning–based image analysis / computer vision, preferably using microscopy data Strong programming skills in Python Additional background in AI and machine learning
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in vivo genetic mouse models, advanced live and intravital imaging, engineered microchip models, primary cell co-culture systems and novel microscopy and analysis methods. The research will provide
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in vivo genetic mouse models, advanced live and intravital imaging, engineered microchip models, primary cell co-culture systems and novel microscopy and analysis methods. The research will provide
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lineage cells and CNS health in aging and repair, using advanced in vivo and in vitro models combined with cutting-edge molecular, imaging, and transcriptomic approaches. About the Role The doctoral
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the function of oligodendrocyte lineage cells and CNS health in aging and repair, using advanced in vivo and in vitro models combined with cutting-edge molecular, imaging, and transcriptomic approaches. About
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techniques such as mouse models, in vivo immune cell functional assays, flow cytometry, cell biology, metabolic assays, imaging and omics-techniques (next generation sequencing). Applicants should possess a
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artificial intelligence/geospatial AI, methods of machine learning and deep learning development of computer vision applications and image recognition methods analysis and production of big data, including