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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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at the Max-Planck-Institut für Kohlenforschung in Mülheim/Ruhr Project 3: “Atomistic Investigation of Chemomechanical Processes in the Fe–O System” under the supervision of Prof. Bitzek, Microstructure and
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environmental geophysics. This PhD project aims to advance the process-based understanding of SSF by combining state-of-the-art geophysical methods with controlled field experiments and numerical modeling
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Course location Hamburg Description/content The Cluster of Excellence "CUI: Advanced Imaging of Matter", which is funded by the German federal and state governments, combines projects in physics
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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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of infectious disease. Our laboratory also offers a wide range of further methods and technologies (organoids, organ-on-chip, diverse sequencing approaches, confocal imaging etc.). Thus, students with an open
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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 approaches and explore and tweak them until they work. The lab
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
3D and image-based computer vision Experience implementing 3D computer vision algorithms and training end-to-end machine learning models (from data collection and design to evaluation) Knowledge and
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al. (2014), EMBO J), the laboratory has more recently employed state-of-the-art genome editing, tailored cellular models and advanced proteomics and imaging to further define the substrate spectrum
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track