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neuroscience. We are part of the Division of Cell Biology, Neurobiology and Biophysics within the Department of Biology . Our division hosts the state-of-the-art Biology Imaging Center , which offers technical
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learning has strong potential for computer vision, from hyperbolic image segmentation [2] to hyperbolic tree embeddings [3] and hyperbolic vision-language models [4,5]. [1] Nickel, Maximillian, and Douwe
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for automatic segmentation and morphometry of histological images; - Compare the predictive value of AI-driven image analysis with clinical and biomarker data; - Collaborate with international experts in medical
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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the Division of Cell Biology, Neurobiology and Biophysics external link within the Department of Biology external link . Our division hosts the state-of-the-art Biology Imaging Center external link , which
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using deep learning and AI-driven image analysis. You will: - Analyse pre-implantation kidney biopsies according to the Banff criteria; - Apply AI methods for automatic segmentation and morphometry
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to advance 3D imaging methods for neuroscience. Your colleagues: An interdisciplinary team working across the Cognitive Neuroscience Department and the Mental Health and Neuroscience Research Institute
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of translation is crucial for controlling protein levels and guiding development. In the Ruijtenberg lab, we study these mechanisms using a combination of genome-wide sequencing and single-molecule imaging
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. Besides this, you will work on scene understanding using RGB and possibly thermal and radar images, including based on object detection and image segmentation, and collaborate effectively with other
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the Multiscale Imaging of Brain Connectivity section (CBClab) within the Department of Cognitive Neuroscience (Faculty of Psychology and Neuroscience, Maastricht University), and in the division for Neuroscience