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from serial MRI scans in the future, which are processed using deep-learning techniques in the group of Prof. Boudewijn and Dr. Stoel. Your analyses will contribute to understanding how systemic and
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Computer Science, Machine Learning, Operations Research or a related technical field. Strong background in deep learning with a motivation to advance fundamental techniques. Excellent analytical, problem-solving
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transparent and intelligible. Although explainable AI methods can shed some light on the inner workings of black-box machine learning models such as deep neural networks, they have severe drawbacks and
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of black-box machine learning models such as deep neural networks, they have severe drawbacks and limitations. The field of interpretable machine learning aims to fill this gap by developing interpretable
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workings of black-box machine learning models such as deep neural networks, they have severe drawbacks and limitations. The field of interpretable machine learning aims to fill this gap by developing
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this project, you will combine a deep knowledge of physical chemistry with robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning
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. You'll be part of the Tactile Machines Lab, which is a dynamic, interdisciplinary group of researcher bringing together expertise in robotics, sensing, machine learning, biomechanics, and haptics
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expertise in robotics, sensing, machine learning, biomechanics, and haptics. The project is funded by a NWO VIDI grant to the PI and provides financial security, access to state-of-the-art equipment, travel
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, working closely with AI specialists and data scientists. Methodologically, you will explore advanced deep learning approaches, including convolutional and transformer-based architectures, as well as methods
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of machine learning (including deep learning) algorithms to predict links between gene clusters and metabolites, and to predict antimicrobial activities associated with these Collaboration with international