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Electrical Engineering, Computer Science, or a related discipline. A research-oriented attitude. Solid background in machine learning and optimization methods. Knowledge and experience in (wireless
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manipulation, topological quests in magnetism, and applications for energy efficient computing? Join us as a PhD candidate to develop magnetic topology on demand! Information Topologically-protected conductors
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is looking for an aspiring PhD candidate to research causal machine learning and uncertainty quantification for Earth Observation time-series. Currently, predictive AI in Earth Sciences relies heavily
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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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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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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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, 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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. Through this research, you will contribute to the healthcare of the future and positively affect the lives of thousands! Job description We seek two highly motivated PhD candidates for this project, one
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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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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