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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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youth in schools, including social media data donation. As a PhD candidate, your tasks will include: instrument selection; setting up the social media data donation in collaboration with experts
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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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(LLMs) and state of the art methods in NLP. Has a demonstrable interest in misinformation countering or climate communication. Is willing to acquire knowledge of Social Network Analysis methods and
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., machine learning, stochastic dynamic programming, simulation). Affinity with (food) supply chain management is preferred. To collaborate with and to co-supervise MSc thesis students and internship students
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depth. You organise your work efficiently, take initiative, and are able to work independently when needed. You’re open to feedback and eager to learn from it, and you enjoy collaborating within
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team consisting of scientific staff and PhD candidates from different disciplines and will collaborate with a small team of software developers working on AI prototypes and the required supportive
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consortium; form interdisciplinary collaborations across fields and geographical locations within the Netherlands; acquire skills by active participation in science communication activities, interacting with
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will collaborate with researchers from various disciplines at iHub, Radboud’s interdisciplinary research hub on digitalisation and society. Lastly, you will also collaborate with other researchers from
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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Fundamental Techniques in Table Representation Learning in collaboration with the University