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preserving signals at test time. This project investigates this type of learning setting in crowded mingling events where access to high fidelity data may normally be considered too privacy invasive. It will
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Are you curious about how people learn from each other? Do you love computational modelling? Join our interdisciplinary team in Amsterdam! We are looking for a PhD student for the project "Social
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Join us in advancing the frontier of plant sciences and making a tangible impact on agricultural resilience through the power of machine learning! We are seeking a highly motivated PhD candidate
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Research Infrastructure? No Offer Description Work Activities The goal of the project is to develop new machine learning frameworks for high-resolution optical imaging and metrology. You will use the new
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evaluate products with a sustainability component. The challenge Reinforcement Learning (RL) has become a popular paradigm for automating decision-making under uncertainty in complex environments. Although
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neural mechanisms of how the brain addresses some of the most fundamental challenges: perceptual decision making, inference, learning, attention and probabilistic/statistical computation. Your research
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to computational cardiology. In this project, you will combine advanced physics-based models of the human heart and vasculature with the latest breakthroughs in machine learning to develop scalable and robust
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. The PhD position is part of the sub programme “Living Lab Learning Environments”. Aim is to develop a scientifically grounded co-creative approach to innovation which is reproduceable and scalable. It aims
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that leverages in-memory computing principles for efficient online learning. Background: The field of neuromorphic computing seems to offer a transformative solution for achieving intelligence at the edge. By
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mission planning often rely on predefined trajectories or reactive behaviours, limiting their versatility and robustness in real-world scenarios. In contrast, integrating planning with novel learning