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22.10.2020, Wissenschaftliches Personal PhD and PostDoc Positions in Visual Computing & Artificial Intelligence: we are looking for highly-motivated PhD students and PostDocs at the intersection
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 22 days ago
robust single cell-based foundation models on digital pathology images and will combine AI with our latest Deep Visual Proteomics workflow. For more information: group.szbk.u-szeged.hu/sysbiol/horvath
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Mechanobiology, Stem Cell and Bone Marrow Niche Biology, or a related field Professional experience in cell mechanics research Professional experience with confocal microscopy and data visualization Professional
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molecular analysis of the detected tumor clones. The postdoc (f/m/x) will build robust single cell-based foundation models on digital pathology images and will combine AI with our latest Deep Visual
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of chromosomes and specific DNA sequences within the nucleus influences gene expression by visualizing nuclear architecture combining molecular biology, biochemistry, and super-resolution imaging methods
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
microscopy. We investigate how the spatial organization of chromosomes and specific DNA sequences within the nucleus influences gene expression by visualizing nuclear architecture combining molecular biology
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-based modeling methods, or continuum mechanics, especially blood flow and transport modeling. Knowledge of AI and OpenGL-based visualization techniques and/or image analysis methods is an advantage
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D