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candidate, you will investigate the learning capabilities of feed-forward and recurrent models of neural circuits with various degrees of biological plausibility, with a focus on: Transferability of
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, simulations and cutting-edge data to uncover the origins of black holes and neutron stars, linking theory with the latest discoveries in this rapidly growing field. It has been just over a decade since the
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towards a new conceptual model that explains the individual dynamics of fatigue. The project will start with an analysis of already-collected data. You will use several forms of time series analysis
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of core web technologies. You have solid experience in Python and JavaScript programming languages. You preferably have experience with building and using machine learning models. You care deeply about
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, viscosity, and surface or interfacial tension. We will train a range of AI models to allow us to predict these properties from the chemical structure alone. Once established, we will expand the self-driving
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at restoring motor function in models of motor disorder. Some part of the role may involve teaching and up to 0.1 FTE of your time may entail teaching activities. A fully funded PhD position is available
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of semantics, pragmatics, philosophy of language, conversational analysis and dialogue modelling), the series of experiments will result in four journal papers, to be integrated into a dissertation. You will
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Contact City Nijmegen Website http://www.ru.nl/ Street Houtlaan 4 Postal Code 6525 XZ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo
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about this position? Prof. M. Vermeulen (Michiel) michiel.vermeulen@ru.nl Last modified: 03 December 2025 Share this page Facebook WhatsApp Mastodon Twitter LinkedIn E-mail
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Code6525XZStreetHoutlaan 4Geofield Contact City Nijmegen Website http://www.ru.nl/ Street Houtlaan 4 Postal Code 6525 XZ STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket