Apply by December 15, 2024 for full consideration
The Nonlinear Systems and Control group at Aalto University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems. The research group is seeking a talented PhD student with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe & robust control, and learning for dynamics & control.
The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees on performance and safety, for example, through the efficient computation of Lyapunov and barrier functions, forward and backward reachable sets, optimal value functions etc. The broad goal is to build upon recent developments in learning Operator Theoretic representations of dynamical systems that focus on model interpretability, scalability to high dimensions, and data efficiency. The exact direction of the research is chosen depending on your experience and interests. Please relate clearly to some of the research topics in your Letter of Motivation.
Outstanding researchers from the areas of Control Engineering, Robotics, Machine Learning, AI, and related areas including Optimization, Mathematics and Physics are welcome to apply. The candidate is expected to conduct independent research and should have strong analytical skills as well as be fluent in spoken and written English. Successful candidates will have the opportunity to collaborate with the vibrant Aalto research community, including the Intelligent Robotics group and the Mobile Robotics group, as well as the Finnish Center for Artificial Intelligence. The group also actively collaborates internationally with top institutions in the US and Sweden.
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