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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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. 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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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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a comprehensive multi-perspectives analysis approach, essential to track the impacts of the characteristics in different scales of the investigated processes on their overall techno-economic
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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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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted
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stress. We want to understand how mechanosensitive membrane microdomains maintain normal cellular processes and how changes in their structure and biophysical properties lead to diseases. Your profile
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the selection process, consideration will be given to the applicant’s research plan, previous academic performance, international orientation, research merits, the duration and progress of any previous funding
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field. Existing skills and knowledge in electronic device nanofabrication and clean room processing of 2D materials (required). Skill sets of handling low-temperature and ultra-high vacuum systems