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Field
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Chair of Biological Imaging 02.02.2026, Academic staff We are looking for a researcher (m/f/x) ready to try new techniques and approach and explore and tweak them until they work. The lab The Stiel
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/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 packages
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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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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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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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the excellence cluster Your profile PhD in physics or in a related discipline experience in phase contrast or coherent X-ray imaging advanced programming skills in a high-level computer language (Python or related
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imaging. The Professorship for Machine Learning at TUM works on machine learning, artificial intelligence, and information processing, with a current focus on foundation models, data-centric research, and
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evaluation routine for area detection of microscope images of salt solutions during solidification Linking the time curves of the automated area evaluation and simultaneously recorded heat flow signals of a
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Max Planck Institute for Medical Research, Heidelberg | Heidelberg, Baden W rttemberg | Germany | 15 days ago
Developing new fabrication processes for CaF₂, sapphire, and BK glass Collaborating closely with industry partners in areas including lasers, imaging cameras, and display technologies Preparing and supporting
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for BlueMaterials?, bridges the different techniques developed within the cross-area imaging and gives support to all researchers dealing with image processing challenges. By focusing on automation and enabling