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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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science and information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image
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of data scientists, software engineers, and experimental researchers on topics including: Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g., SEM
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of Electrical Engineering and Computer Science School of Art and Design Course language German and English Financial support No Structured research and supervision Yes Research training / discussion Yes Career
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dynamic, interdisciplinary team that combines science, sustainability, and technology to create a better future. Help shape the next generation of sustainable materials inspired by nature's most powerful
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imaging. Your Profile: * Master's degree in Computer Science, Electrical and Computer Engineering, Mathematics, Physics, or a related field * Strong background in mathematical and computational sciences
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the research areas of Infection Medicine and Microbiology, Immunology, Oncology, Neurosciences, Pharmacology/Cardiology/Vascular Medicine, Imaging Technology and Biomedical Engineering, amongst others. A large
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with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational