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problems, numerical mathematics, optimisation, machine learning and imaging physics, with applications ranging from medical and industrial imaging to geophysics. For more information, please visit
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. In this PhD project, you will investigate foundation models for automotive imaging radar. The goal is to learn general radar representations from largely unlabelled data that can generalize across
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scale radar datasets with high quality labels remain scarce. In this PhD project, you will investigate foundation models for automotive imaging radar. The goal is to learn general radar representations
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research combines inverse problems, numerical mathematics, optimisation, machine learning and imaging physics, with applications ranging from medical and industrial imaging to geophysics. For more
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planning and decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch
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learning, and logical reconstruction techniques. The research investigates how multimodal imaging modalities - including scanning electron microscopy (SEM), photon emission microscopy (PEM), and focused ion
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goal of your PhD project will be to develop combined X-ray and visible-light imaging technologies and machine learning methods for high-throughput inspection tasks. The work will include the development
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), Computer Science (Machine learning, Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Your project is part of the DUAL-IMPACT project, which focuses on the development
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(preferably in Python, including deep learning frameworks such as PyTorch); affinity with medical image analysis and computational modeling; experience with neural networks for image analysis, generative
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computer vision, deep learning, and logical reconstruction techniques. The research investigates how multimodal imaging modalities - including scanning electron microscopy (SEM), photon emission microscopy