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-physical systems secure and resilient in the presence of uncertainty and cyber-physical attacks? Then you may be our next PhD candidate in resilient and learning-based control of cyber-physical systems
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degree in AI, Computing Science, Mathematics, or Data Science. Strong coding, communication and organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch
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organizational skills. Demonstrable experience with using machine learning packages (e.g., PyTorch). Completed academic courses in AI or machine learning. We consider it an advantage if you bring experience with
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to make a start with your teaching portfolio and dedicate 10% of your working time to teaching in the psychology curriculum. Would you like to learn more about what it’s like to pursue a PhD at Radboud
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17 Apr 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Systems engineering Researcher Profile
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systems increasingly provide personalized recommendations in domains such as nutrition and lifestyle. However, many recommender and prediction systems rely heavily on opaque machine learning techniques
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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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and Delft University of Technology. Curious to learn more about the project? Feel free to visit our website , where you’ll also find other exciting PhD opportunities related to this collaboration. In
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diversification and change we see across languages today. Job description This 4-year PhD project will use group communication games and artificial language learning experiments to investigate the role of social
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. You will combine technical work on machine learning with qualitative analysis of how AI systems are interpreted and used in organisational decision-making. Join the Human-Centred Computing group