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(or equivalent) in Computer Science, Artificial Intelligence, Engineering or a closely related field; Solid background in machine learning and/or evolutionary optimisation; strong programming skills (Python/C
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artificial intelligence, computational cognitive science, human-computer interaction, computer science, information systems, or another relevant field. - A keen interest in pursuing interdisciplinary research
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented 2 PHD-STUDENTS IN NEUROAI OF DEVELOPMENTAL VISION (M/F/X). Job description The Curriculum
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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language
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collaborative, diverse team. This is a unique opportunity to contribute to the foundations for tomorrow’s machine learning. Your job In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic
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, creativity, rigor, ownership, and excitement to push research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, data management, and
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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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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant