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science, environmental modelling, geosciences, or related field with strong quantitative focus; Strong background in machine learning methods such as neural networks and transformers; Knowledge on handling
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this specific structured data. How can we perform inference tasks to learn hidden patterns, like community structure or hidden hierarchies? How can we incorporate domain knowledge to design interpretable models
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on: Data-driven practical feedback linearization, enabling control of nonlinear systems under uncertainty and partial model knowledge, Learning dynamics within control loops, integrating adaptive and
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coding skills in Python. You are strongly motivated to acquire advanced skills in Python and in the use of high-performance computer systems You have affinity and preferably experience with system dynamics
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a Master’s degree in cognitive neuroscience or an adjacent field (psychology, biology, biomedical sciences, computer sciences, or any other relevant MSc). You have a strong interest in fundamental
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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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, and/or machine learning. Preferably you finished a master in Computer Science, (Applied) Mathematics or related masters. Expertise in the field of visualization or visual analytics. You have good
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PhD position ‘Courage to Correct: Balancing Error Prevention and Learning in Strategic Crisis Teams’
Vacancies PhD position ‘Courage to Correct: Balancing Error Prevention and Learning in Strategic Crisis Teams’ Key takeaways In high-stakes crises, strategic teams often aim to avoid errors at all
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to learn more about the project, and perhaps our group? Feel free to browse our webpages: About our department: QCE department . About our group: Computer Engineering Lab . Job requirements For this position
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knowledge of and/or experience with validation of prediction models (regression or supervised machine learning), health technology assessment, decision curve analysis, and/or value-of-information analysis