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the "Mercury in the solar wind" ERC project at the Finnish Meteorological Institute. The PhD student will apply our global particle-based models to study the solar wind influence on Mercury and its environment
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is part of the newly funded Research Council of Finland project Redefining Inner Boundaries in Solar Wind Models (RIB-Wind), led by Dr. Stephan G. Heinemann. The preferred start date is October 2025
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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
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. The handling of unseen languages remains without real solutions, despite the research community having made a few practical excursions, such as using trash language models or confidence thresholds
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economy. The group aims for analyzing the technologies within this context through experimental and systematic model-based analyses. Scientific publications by the group can be viewed in Publications and
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is to apply theories, models, and methods from psychology to improve Human-AI interaction. Your network and team The Aalto Engineering Psychology Group concentrates on research in human-AI interaction
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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages
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development. The successful candidate will contribute to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model