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Field
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candidate will facilitate code collaboration within the Modelling of Atmospheric Processes (MOD) department and, in particular, manage IAP code contributions to the upper atmosphere components of the ICON
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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Chair of Biological Imaging 27.02.2026, Academic staff We are now seeking a highly qualified and motivated Ph.D. student (f/m/x) to drive the development of novel optical technologies addressing
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Chair of Biological Imaging 27.02.2026, Academic staff We are now seeking a highly qualified and motivated postdoctoral fellow (f/m/d) to drive the development of novel optical technologies
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the case of challenging environmental conditions, the method of multi-scale parallel single-pixel imaging has the potential to enable breakthrough advances. The “image processing and AI” group contributes
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(preparation and staining (IF, IHC), confocal and fluorescence microscopy, analysis and evaluation) Experience with quantitative analysis of imaging or physiological data (e.g., microscopy, cardiac imaging
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imaging systems and ensure the optimal deployment and networking of sensors to efficiently process and analyze the resulting data streams. In this way, we support people in decision-making, process
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: to make the world of tomorrow safer. Be part of change Implementation and application of computer vision approaches, including: object detection (e.g., using YOLO, RT-DETRv2, etc.) image classification
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immune responses By combining transcriptomics, immunohistochemistry, advanced imaging, and physiological assays across, we aim to elucidate the fundamental processes underlying the evolutionary success and
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such as 3D tissue imaging, molecular profiling are combined with AI tools to decode the complexity of tissues and shed light into cancer biology. Our interdisciplinary team — comprising biologists