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Field
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Biology, Biomedical Imaging, Biochemistry, Physics, or a related field A strong interest in biomedical imaging, contrast agent development, immune cell tracking, and data analysis Previous experience with
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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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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
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degree in biomedical sciences or related life science discipline We are looking for candidates with hands-on experience or a strong interest in spectral imaging techniques, confocal microscopy, and
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin
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cells provide new means for studying human health and disease in the lab. These systems may ultimately reduce the cost of drug development and accelerate biomedical research. Multi-material 3D printing
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different types of exercise limitations and muscle changes. Additionally, you will collect new data using non-invasive techniques like magnetic resonance imaging (MRI) and near-infrared spectroscopy (NIRS
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
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Chair of Biological Imaging 07.08.2025, Wissenschaftliches Personal We are now looking for a highly qualified and motivated researcher with an engineering or physics background (f/m/x) and a