17 image-coding-"Foundation-for-Research-and-Technology-Hellas" PhD positions at Technical University of Munich
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) on Foundation Models and/or Deep Learning for Imaging Problems. The Professorship for Machine Learning at TUM works on machine learning, artificial intelligence, and information processing. The current focus is
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heterogeneity; namely non-iid and domain shift, e.g. multi-modal data acquired by different scanners and imaging protocols. Publish and present scientific results at international conferences and high-impact
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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27.04.2021, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at Technical University Munich invites applications for the position of a Research Assistant (m/f/d) for performing fundamental research in the frame of the project AI-CHECK funded by the...
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15.04.2025, Wissenschaftliches Personal The Lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is inviting applications for a fully funded PhD position in interpretable machine
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heat measurements and imaging mass spectrometric methods. The labeling of the organic compounds with the stable isotope 13 C will allow tracing its impact on organo-mineral interactions and microbial
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Chair of Biological Imaging 11.07.2023, Wissenschaftliches Personal We now seek a highly qualified and motivated PhD student (f/m/d) to design, develop, and test novel optoacoustic sensing platforms
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models. Your tasks: Research, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in
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working in interdisciplinary and international teams and have image processing or image analysis skills. In addition, you are able to express yourself confidently both orally and in writing in English. What
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to study translational aspects of cancer (single-cell sequencing of immune cells, organoid co-cultures, cellular engineering via CRISPR/Cas9 technology, in vivo imaging, advanced animal models of allo-SCT