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on developing new ML approaches to challenging quantum problems, with a strong focus on making these approaches interpretable, reliable, and scalable. In this position, you will learn about state-of-the-art deep
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models. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience a and strong deep learning programming skills. Ability to work in an
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for Sustainable Energy, researchers from academia and industry develop, implement and evaluate new deep reinforcement learning methodology to solve sustainable energy challenges. Key responsibilities The lab is
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Are you looking for a PhD position where you develop state-of-the-art machine learning methods for the life sciences (geometric deep learning, transformer-based approaches, ...) with a focus on
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binders that engage with therapeutic targets or efficient (bio)catalysts for synthetic applications. By seamlessly merging cutting-edge directed evolution, next-generation sequencing, and deep learning
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simulations with deep learning neural networks and swarm robots, virtual reality experiments, animal communication research, and more. In a range of projects, we show that languages can effectively be seen as
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per second. This creates new opportunities for surgical guidance, and 4D functional imaging of the brain. Integrating deep learning (AI) into these new techniques is critical, due to the large amount
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deep scientific curiosity, have excellent experimental and quantitative skills and possess a drive to learn and develop new methods and concepts. You have excellent verbal and written communication
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Organisation Job description Are you passionate about combining the directed evolution of diverse biomolecules with deep learning approaches and contributing to the development of better (bio
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that can be used for training machine learning and deep learning models. You will work in tight collaboration with other researchers in Nijmegen, Delft and at the Hubrecht Institute (van Oudenaarden group