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., food processing, bioconversion and fermentation processes) Self-supervised learning for multimodal sensor data (e.g., spectroscopy, hyperspectral imaging, 3D point clouds, and other high-dimensional data
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, or Engineering. Do you have experience of numerical modeling of atmospheric processes and are you already familiar with meteorological topics? Can you program in Python or Julia? Ideally, you also have some data
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directly on our real test vehicles (see image) for automated driving. Application of modern software engineering approaches (e.g., agile methods, model-based development, CI/CD pipelines) in concrete
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prevention Cell biology and tumor biology Developmental Biology Epidemiology Genomics Medical Technology Metabolomics Molecular imaging and radio oncology Redox biology Tumor immunology and immunotherapy
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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