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, particularly artificial neural networks, and deep learning? And you would like to continue your research on clinically relevant topics? If yes, then Maastricht University has a new challenge for you! Postdoc
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, normalizing flows, VAEs, generative transformers, or related methods. Strong programming skills and experience with modern deep learning frameworks. Experience with large-scale model training, distributed
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| Classification CBA: §48 VwGr. B1 lit. b (postdoc) Limited contract until: 14.09.2032 Job ID: 6013 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of
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calculations Machine Learning/Deep Learning techniques. Education and Experience: A PhD in physics, astronomy, or a closely related field must be completed before the position begins. Additional information
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, the Peabody Museum, or more technical parts of the University for periods of time to learn about both research and operational workflows. Connections with the Wu Tsai Institute, the AI at Yale program, the Data
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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learning and deep learning techniques to the biological sciences. The ideal candidate will have expertise in artificial intelligence, with a specific focus on deep learning applications in structural biology
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
but are not limited to: development of new AI architectures for biology and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and
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including electrical/electronic engineering or similar. Experience in federated learning/deep reinforcement learning is preferred. At King’s, you will join a research-leading and multi-disciplinary team led