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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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. This international, multidisciplinary project aims to design, implement, and evaluate Hybrid Blue-Green Infrastructure (HBGI) solutions that combine the benefits of natural ecosystems with the protective functions
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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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can focus on learning for planning, risk-aware motion planning under uncertainty, learning of interaction models, multi-robot learning, multi-modal prediction models, or other related topics
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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wide range of resources and is mostly not publicly available. While sharing proprietary data to train machine learning models is not an option, training models on multiple distributed data sources
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advancing image-guided precision irradiation and realistic disease modelling. As postdoctoral researcher, you will contribute to cutting-edge developments in preclinical CT imaging, precision irradiation, and
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Research Institute for Oncology and Reproduction, the MAASTRO Physics Research Division plays a leading role in advancing image-guided precision irradiation and realistic disease modelling. As postdoctoral
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. The focus involves expertise in energy modeling, optimization and analyzing diverse energy mixes, primarily emphasizing hydrogen-based systems. As we move toward cleaner energy systems, the way we plan and