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In this role, you will be responsible of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with
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learning Deep learning model generalisation techniques Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object
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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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learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In this role, you will
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at 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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settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on obtaining external funding and project
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of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In
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Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on
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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