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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 candidate will be
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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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around us? At Maastricht University, you will investigate how individuals differ in predictive processing by combining behavioural and neural testing with computational modelling. Together with colleagues
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role of neural rhuthms for inter-area brain network communicartion PHD2: The neural code for multi-item representation in working memory PHD 3: The dynamic interplay between brain and bodily rhythms in
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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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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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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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. 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 annotations). The research will be conducted
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the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics its processing capabilities but also its adaptability, leveraging early
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identification of biological sounds using passive acoustic data. Passive acoustic monitoring will be conducted with species identification based on a neural network trained and tuned to the turbulent waters