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experience with imaging, image processing, and/or visualization, as well as excellent programming skills. You must have a relevant Master's degree in computer science, electrical engineering, imaging science
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scale hydrological models The project offers the unique opportunity to connect novel processing and inversion techniques to experimental data from different regions and link the findings to relevant
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data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems
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: Experience with crystallization processes, soft matter physics, or porous media Familiarity with imaging techniques (optical/electron microscopy, X-ray tomography, or spectroscopy) Experience with cultural
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-driven life science framework. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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multiphysics - Strong interest in experimental techniques and analysis of experimental data - Skills in programming and signal and image processing - Taste for interdisciplinary environment: physics, chemistry
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challenges of our time is straining our ability to exert cognitive control. Our Digital Age is characterized by a continuous flow of multi-source information. One of the pinnacle strategies to process that
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have strong programming skills in Python; You have knowledge of medical image processing, and machine learning and deep learning techniques; Written and spoken proficiency in (scientific) English is
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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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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 8 days ago
twenty project teams, located in Nancy, Strasbourg and Saarbrücken. Its activities occupy over 400 people, scientists and research and innovation support staff, including 45 different nationalities