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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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maintain close collaborations with the Jheronimus Academy of Data Science (JADS) in ‘s-Hertogenbosch. The research group consists of about 70 researchers covering a broad range of topics relevant
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implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning
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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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multimodal deep learning models that integrate imaging and clinical data to personalize treatment and follow-up strategies. In the Netherlands, around 75% of patients with an abdominal aortic aneurysm (AAA
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highly multidisciplinary exploration within a diverse and collaborative team environment. We're looking for colleagues who embrace challenges with enthusiasm and are team players. If you're passionate
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the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both
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expert collaborations. We have a wide range of deep learning-based projects ranging from fundamental AI research to translational evaluation of existing algorithms. Check our website for more information
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multimodal deep learning models combining CT imaging and clinical data, trained on the unique RADAR consortium database . These models will be validated in close collaboration with clinical and industrial
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of Science at UvA. What are you going to do? The aim of the project is to use advanced Machine Learning techniques to predict the anharmonic vibrational spectra of large Polycyclic Aromatic Hydrocarbon (PAH