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Museum fuer Naturkunde, Leibniz Institute for Evolution and Biodiversity Science | Berlin, Berlin | Germany | about 15 hours ago
and molecular machinery, first discovered by meticulous electron microscopy in the past decades. More recently, this has been complemented by genetic studies of their development and differentiation in
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6 Apr 2026 Job Information Organisation/Company Forschungszentrum Jülich Department Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons (ER-C) Research Field Biological sciences
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for research and employees from all over the world. The Core Facility Cellular Imaging at the FMP is looking for a Technical Assistant for Electron Microscopy (m/f/d) (Ref 02/2026) The position is full-time as a
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The Innovative Electron Microscopy Department develops and applies electron microscopy methodologies for nanoscale and atomic-resolution characterization of functional materials and their interfaces
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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or aqueous batteries · solid knowledge of electrochemistry or relevant project experiences · experiences with operating scanning electron microscopy/focused ion beam · a high level of
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recrystallisation experiments using advanced analytical methods such as Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and synchrotron-based
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. The defects will be analysed by using a combination of advanced transmission electron microscopy and spectroscopy methods, as well as Raman spectroscopy and photoluminescence mapping. Your key tasks
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Develop new machine learning
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time