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of compensating for nonlinear PA characteristics under dynamic operating conditions. Advanced machine learning and neural network approaches will be explored to improve linearization performance while reducing
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the funded line of research “Structural Neural Networks”. 1.2. Unit in charge of the line of research: Department of Computer Science and Artificial Intelligence. 1.3. The first project in which the successful
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optimally combined to deliver models with extremely constrained compute and memory footprints without compromising performance. This includes training spiking neural networks with multiple plasticities
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interview and positive feedback about Radboud University from my network, I decided to take the leap and move to Nijmegen. It was a risk to leave my Norwegian comfort zone, but I am extremely satisfied with
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on developing hybrid traffic flow models that combine physical modelling principles with machine learning approaches, such as Physics-Informed Neural Networks (PINNs) and machine-learning-enhanced traffic models
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Neural Networks (PINNs) and machine-learning-enhanced traffic models. You will: Develop next-generation hybrid traffic flow models that combine traffic theory with machine learning Investigate Physics
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be used to identify clinically relevant indicators of neurodevelopmental risk. Depending on the direction of the research, the project may explore techniques such as convolutional neural networks (CNNs
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on the intersection of learning theory, PDEs, and systems & control, likely using RKHSs (or similar function spaces), Koopman operators, and neural networks to study interesting classes of controlled PDEs, develop
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learning frameworks such as PyTorch (required) Knowledge of neural networks, transformers, and representation learning techniques (desirable) Experience in time-series modelling, biosignal analysis
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neural networks) to design and optimise integrated photonic devices and metasurfaces. This includes building automated workflows that link electromagnetic simulation tools with AI models to accelerate