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on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order models, designing controllers that exploit
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic
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nature. The PhD candidate will focus on the theoretical and algorithmic development of control methods that combine physical modeling and real-time computation. The work will involve deriving reduced-order
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sufficiently “compact” (i.e. algorithmically small and computationally efficient) to enable incorporation in integrated PED models. The development of these compact models will involve collaboration with several
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such as textiles. 2. Proven ability to develop and implement advanced motion-planning algorithms and real-time control schemes, ideally demonstrated through digital-twin simulations and hardware-in-the-loop
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sector. How do we protect fundamental rights when algorithms help decide on who receives public benefits, how to perform enforcement or how to enact environmental policy? What is the role of the state, and
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more
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-research-projects-awarded-through-open-competition-domain-science-m-programme ). Responsibilities and tasks: Development of novel electrocatalysts for N2 fixation. Fabrication of single cells with targeted
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data