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collaborative learning processes in specific knowledge domains in educational sciences and AI tools and infrastructures. Different types of AI (generative and domain specific intelligent technologies) change
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related to heart failure and cardiovascular biology. Develop and apply machine-learning and deep-learning approaches to identify disease-associated cardiomyocyte subtypes, cellular trajectories, and
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materials discovery with cutting-edge high-throughput platforms, robotics, machine learning, and autonomous experimental workflows. Access World-Class Facilities: Based in the Department of Chemical and
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processes under different biological conditions. Apply statistical learning, deep learning and probabilistic modelling approaches to large-scale cancer datasets. Evaluate and benchmark computational methods
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deep insight and interest in investigating the interaction between collaborative learning processes in specific knowledge domains in educational sciences and AI tools and infrastructures. Different types
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++, Java, Julia, or other competent languages. A good record of publications in reputable peer-reviewed journals in maritime transport, logistics management, machine learning, deep learning, and optimization
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of neurodevelopment and its disorders. Great technical strides are prying open the black box of the brain, while artificial deep-learning algorithms can now defeat Go masters. Yet, we are still far from understanding
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Location: The Francis Crick Institute, London Short summary We are seeking an ambitious Postdoctoral Fellow to develop the next generation of deep mechanistic models (DMMs; Fabrini & Fröhlich
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with deep insight and interest in investigating the interaction between collaborative learning processes in specific knowledge domains in educational sciences and AI tools and infrastructures. Different
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involves development of deep learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation, as well as new measures of privacy and