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imaging) and the possibility to learn and apply genome-wide R-loop mapping techniques. This project will be part of the RTG on R-loop Regulation in Robustness and Resilience (4R). More information can be
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achieved via the implementation of state of the art multicolor flow cytometry analyses, imaging, omics techniques (e. g. single cell sequencing and proteomic). Theoretical and practical knowledge in
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. Scanning probe microscopes (SPMs) powered by machine learning are expected to enable the autonomous and label-free nanoscale structural and functional (mechanical and electric) imaging of living cells and
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optical and chemical tools with classical genetic techniques and advanced image analysis to study cytoskeletal force dynamics quantitatively. A key focus is understanding how microtubules contribute
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) on Foundation Models and/or Deep Learning for Imaging Problems. The Professorship for Machine Learning at TUM works on machine learning, artificial intelligence, and information processing. The current focus is
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patch-clamp electrophysiology, multielectrode arrays (MEA), molecular cell identification, and single- and two-photon imaging. This role offers an excellent opportunity to develop expertise in
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DWI-Leibniz-Institute für Interaktive Materialien e.V. | Aachen, Nordrhein Westfalen | Germany | 3 months ago
engineering, biochemistry, or related field Several years of experience in the field of cartilage and cartilage repair Extensive experience in cell culture, cell imaging, and omics Experience with mesenchymal
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Max Planck Institute for Evolutionary Biology, Plön | Plon, Schleswig Holstein | Germany | 3 months ago
Job Code: 05-2025 Job Offer from February 07, 2025 The Max Planck Institute for Evolutionary Biology in Plön. Germany, is an internationally oriented institution whose research focuses