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of Europe's most exciting research initiatives using worldwide unique imaging infrastructure. Collaborate with a dynamic, interdisciplinary team that combines science, sustainability, and technology to create a
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Chair of Biological Imaging 02.02.2026, Academic staff We now seek a highly qualified and motivated Post-doctoral researcher (f/m/x) to drive the development of a novel quantum enhanced microscope
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world with increasing digitalization and medical needs. Our research integrates materials chemistry, biological processes, physical analysis, process engineering and data science. We collaborate with
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The Leibniz-Institut für Kristallzüchtung (IKZ) is a leading research institution in the field of science & technology as well as service & transfer of crystalline materials. Our goal is to enable
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), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy
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well as an active engagement in the 3RTG activities. Requirements: successfully completed university degree (Master's, Diploma or equivalent) and relevant PhD in Computer Science, Computer Engineering, or related
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data processing, image/signal analysis, and machine learning. ✅ Familiarity with instrument control, calibration, and automation workflows. ✅ Excellent written and oral communication skills in English
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access to the technology Hubs by the SyNergy Cluster of Excellence. These include advanced platforms for single-cell and spatial transcriptomics, high-resolution imaging, multiomics, and neuropathology
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programming for workflow automation and data handling Familiarity with high-content imaging and quantitative analysis is a plus Interest in interdisciplinary approaches at the interface of biology, technology
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
that packages defined RNA cargos and delivers them to specific cell types. STVs consist of a synthetic protein that is assembled from natural and AI-designed protein domains, along with an engineered fusogenic