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- Delft University of Technology (TU Delft); yesterday published
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are currently seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the successful
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics
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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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methods. Specifically, brain samples will be rendered transparent with optical tissue clearing methods and imaged with 3D microscopy techniques, particularly light-sheet microscopy. The vascular network
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robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning and neural networks for chemical property prediction. You will be part