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Your Job Develop machine-learning–based workflows and scientific software for segmentation, species classification, and lineage tracking in multi-species time-lapse microscopy data Optimize models
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compared to identify and evaluate early pathologic processes. Challenging aspects include image segmentation of the lung, lobes, airways, and vascular tree; extending our tissue characterization
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changes during HIV-1 and VEEV infection. To use organoid sections, intact organoids and cells models in this study. Apply advanced image analysis including AI assisted segmentation, classification
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-based modelling -individual support for researchers across BlueMat in solving image analysis challenges, especially segmentation and quantitative extraction Your profile -PhD in computer science
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French National Institute for Health Research (INSERM) | L'Haÿ-les-Roses, Île-de-France | France | 10 days ago
should have experience in quantitative biology and/or bioinformatic analysis, including: Image analysis (cell segmentation, tracking, morphometry analysis) Spatial transcriptomics Single-cell
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, medical-image metadata, and clinical imaging workflows. Experience with image classification, segmentation, temporal modeling, representation learning, multimodal learning, or clinical prediction
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, artificial intelligence, and data-driven discovery. Learn more about the iMIND Study Team: https://dukeeyecenter.duke.edu/imind Be Bold. Join a multidisciplinary research team at the forefront of