53 biomedical-signal-processing Postdoctoral positions at Technical University of Munich in Germany
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made from magnetoelectric materials, which transduce wireless magnetic powering signals into local electric signals that can be used to stimulate neurons. Our multidisciplinary group works in materials
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aneurysms. Arterial geometries are derived from medical scans (e.g., CT) of real patients, which are suitably meshed and processed for numerical treatment using Lattice-Boltzmann methods (LBM). For fluid
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19.07.2022, Wissenschaftliches Personal The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current
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and Ethics in Medicine, we advance ethical practice and theory in medicine, biomedical technology, and public health, driven by the belief that embedding ethics is essential for shaping the future
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via email to applications@mirmi.tum.de quoting “Postdoc Position in Dexterous End-Effectors for 6G Tactile Tele-surgery” in the e-mail subject line. The position will be filled as soon as possible and
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Numerical Mathematics (Chair of Prof. B. Wohlmuth) within the DFG funded SPP2311. Research focus: Biomedical simulations of cerebral aneurysms with Lattice Boltzmann methods. Field of Research: Multiphysics
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talented individuals passionate about AI, Human-Computer Interaction, Eye-Tracking, and their responsible applications. Ideal candidates will have: • An M.Sc. degree (or equivalent) in Computer Science, Game
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to the Technical University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection
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Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By
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04.04.2025, Wissenschaftliches Personal The Chair for Computer Architecture and Parallel Systems (CAPS) offers this position as part of the DARE-project funded by the EuroHPC JU bringing together