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use, providing richer context and a more comprehensive analysis of current complex issues in society. If this fits your expertise and interests, the Interaction Division of Utrecht University is seeking
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traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where possible. This innovative new approach enables more efficient and
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together researchers from TU/e, the University of Twente, and Maastricht University. Working closely with a PhD candidate and the project's supervisory team, you will design, train, and iteratively refine
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in mathematics. The Institute currently comprises about 35 faculty members, 10 Postdocs, 25 PhD candidates, and teaches 500 students. The Institute is internationally recognized for its research in
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the long term. Currently, deep geological disposal is recognised as the only feasible solution for the final disposal of radioactive waste. In the Netherlands, deep plastic clay formations are considered as
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to learn about, (road) network traffic flow theory and simulation. You are interested in mentoring and supporting MSc and PhD students. You are a machine learning enthusiast (and realist). You love coding
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personalisation with polyvocality: adapting to individual visitors while also encouraging engagement with unfamiliar, marginalised, or challenging perspectives. Many current conversational agents and recommender
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and how you would like to address them. What technological innovations in onboard AI will overcome current EO system limitations and enhance autonomous decision making, operational efficiency and
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Russia, especially by minoritized groups. Currently, we seem to observe a rise in the polarization of political opinion, accompanied by a hardening of the tone of political discourse and decreased mutual
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synthesis out of fossil-based and one time use to continuous reuse of polymeric products. Current recycling methods cannot recover high-value polymers from complex waste streams such as multilayer packaging