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model the remarkable learning efficiency of the human visual system. The project is an interdisciplinary collaboration between the the Machine Learning group at CWI in Amsterdam (Prof.dr Sander Bohte) and
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networks, or network science, and relevant background knowledge on methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods
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of Amsterdam. Interested in developing fundamental machine learning techniques for tabular data to democratize insights from high-value structured data? Then this fully-funded 4-year PhD position starting Fall
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data is lacking. With the DataLibra project, we aim to close this gap, by developing AI models and tools for structured data (Table Representation Learning), to help organizations, of any size, domain
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that would give you an advantage) Experience in computational modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning, robotics). Experience in annotation software such as
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faces. At the same time, reinforcement learning is a key technology in artificial intelligence and machine learning that set various state-of-the-art results. In the Reinforcement Learning Lab
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observations. Your major challenge is in model development, and there is room for you to develop machine learning applications in the field of firn modelling. If successful, your work will lay the foundation
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economic impact through simulation modeling. Beyond this unique project, this position offers an exciting opportunity to advance simulation techniques in HTA! Information and application Submit your
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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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of political violence: from the role and effectiveness of sanctions during military disputes to the increasing importance of non-state actors in war, and from the effect of non-governmental organizations