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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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outdoor and cultural opportunities, a vibrant student scene, and an impressive scientific heritage. Position details PhD students will have the opportunity to participate in one of several available PhD
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outdoor and cultural opportunities, a vibrant student scene, and an impressive scientific heritage. Position details PhD students will have the opportunity to participate in one of several available PhD
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learning and signal processing approaches to classify cap types from raw signal traces. Collaborate closely with experimental researchers to guide experimental design and interpret data. Contribute
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reliability of R-Mode, particularly under varying environmental conditions. Key objectives include understanding the physical processes that affect R-Mode signal propagation, quantifying the variability
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balance. Lead data analysis efforts, applying advanced signal processing and statistical techniques to extract meaningful insights from electrophysiological and imaging data. Collaborate with
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with fewer data points and tailored reward functions towards design objectives while generating molecules in 3D. Additional requirements: Doctoral degree (PhD) in computational (medicinal) chemistry
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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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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13.03.2023, Wissenschaftliches Personal We are looking for motivated students to work on the development and implementation of a cheap and scalable ceramic processing concept towards a fully sprayed