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Faculty of Science Researchers and students at VU Amsterdam’s Faculty of Science tackle fundamental and complex scientific problems to help pave the way for a sustainable and healthy future. From forest fires to big data, from obesity to malnutrition, and from molecules to the moon: we cover the...
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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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bovine cells in wave bioreactors, developing a scale-out approach to enable farm-level production; lead the technology transfer from laboratory-scale to the world’s first cellular agriculture farm
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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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Key takeaways To bring computing power to the edge and to make the cloud sustainable, various paradigms for energy-efficient computing are emerging. These paradigms, for example neuromorphic, wave
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, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge multimodal deep learning models that integrate imaging and clinical data
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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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applications from individuals with experience in: Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation techniques
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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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availability of data and connectivity through the Internet of Things create new opportunities to incorporate real-time insights into decision-making, combining tractable modelling with provably efficient