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learning, medical image computing, biomedical engineering, medical physics, or related field Strong Python and PyTorch experience Solid publication record and ability to communicate research results
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learning, chemical intuition, and experimental feedback, you will help reveal the mechanistic origins of high-performance separation membranes and provide design rules for next-generation materials
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they interact and connect with each other. The doctoral researcher will develop computational indicators that capture these patterns from digital communication data, model how learning relationships form and
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the development of novel optical technologies addressing significant biological and medical challenges. The Mission: The successful candidate will play a key role in an ambitious research program focused
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research program focused on developing next‑generation multimodal imaging systems spanning the mesoscopic to microscopic scale. As part of a major research project and supported by extensive national and
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problems. Use the measurement / test data to identify the high-fidelity modelling parameters by solving the inverse problem. Validate the digital model against test scenarios. Perform what-if analyses
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(PhD, 75%, 30h per week). Remuneration is in accordance with the German public tariff scheme (TV-L), salary group E 13. The successful candidates will be part of the Munich Climate Center and the Earth
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biological models. This position involves the optimization, and operation of an innovative multimodal microscope, as well as close collaboration with experts in the biological sciences for its application
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part of an international team Desired Qualifications Familiarity with cloud computing platforms and large-scale data processing German language skills Publications in computer vision or machine learning
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the area of entrepreneurship and family enterprise while participating in the doctoral program. TUM School of Management at TUM Campus Heilbronn invites applications for a Research Associate (m/f/x