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different hardware backends. Design conventional (GPU-based) deep neural networks for comparison. Publish research articles, regular participation in top international conferences to present your work
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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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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 brain signal acquisition Implementing an on-chip neuromorphic processor with a spike encoder and spiking neural network Developing a low-power spike-based transmitter. Setting up measurement systems and
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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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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network project ANT. The objective of Doctoral Networks is to implement doctoral programs by partnerships of organizations from different sectors across
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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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machine learning frameworks such as recurrent neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection
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neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection. Comparison with known analytic methods and