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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image
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of analysis and visualization software Very good written and spoken English skills are required Furthermore, experience in dealing with the ICON model and the scientific utilization of ICON data is an advantage
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procedure Icon Applicants Applicants Icon Foundation Foundation Icon Notification Notification Nomination Examinationapprox. 1-2 months Review Processapprox. 3-4 months Conferral Nomination documents
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recommend checking out two exemplary recent publications (and maybe even the corresponding code and image repositories): You will be involved in writing scientific publications, presenting your research
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key role in gene regulation. By employing omics-based approaches, metabolite tracing, proximity-labelling, and advanced imaging techniques, this project offers a unique opportunity to: Explore how
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project, we highly recommend checking out two exemplary recent publications (and maybe even the corresponding code and image repositories): You will be involved in writing scientific publications
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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-time data acquisition during production, consulting, and prototype manufacturing. We aim to eliminate distortion due to residual stresses during the milling and turning processes using simulations. We
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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