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foundation models, deep machine learning and computer vision. Topics of interest are test-time generalization, embodied grounding, data scarcity and uncertainly modeling. The research is embedded in the VIS
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Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field; a thorough understanding of both information retrieval and deep learning; solid programming skills
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% salary; partly paid parental leave; the possibility to set up a workplace at home; a pension at ABP for which UvA pays two third part of the contribution; the possibility to follow courses to learn Dutch
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work in a consortium consisting of university groups with complementary skills in fluid dynamics and statistical physics (Fluids and Flows, TU/e) and machine-learning techniques (AMLab, UvA), and
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, such as statistical AI (machine learning), symbolic AI (knowledge graphs, reasoning), and human computation (crowdsourcing). By analyzing empirical evidence of human interactions with data and systems, we