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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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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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: this provides capability for accurate and fast modelling of urban drainage, handling the full complexity of flow paths on impermeable surfaces, green space, buildings, pipe networks and BGI features
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are recruiting three PhD students with distinct research foci: PHD 1: The functional role of neural rhuthms for inter-area brain network communicartion PHD2: The neural code for multi-item representation in
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to contribute to foundational research at the intersection of control theory, optimization, and artificial intelligence, with potential applications in energy systems, and infrastructure networks. The successful
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual
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for personal and professional further development. A structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral
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continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: www.fz-juelich.de/en/judocs The opportunity
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Leiden, which will maximize access to learning opportunities, local research networks, and access and facilities. Candidate profile: Applications are invited from outstanding graduates who meet the
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, optimization, and artificial intelligence, with potential applications in energy systems, and infrastructure networks. The successful candidate will become part of a dynamic and internationally connected