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. The work aims at modeling carbon flows, developing solutions for removing and storing greenhouse gases into the built environment, and developing the life cycle assessment method for quantifying multiple
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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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Doctoral Researcher in statistical signal processing. The Structured and Stochastic Modeling Group, headed by Prof. Filip Elvander, conducts research in statistical signal processing, ranging from
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tools, including 4D point cloud modeling and state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with empirical fieldwork in Norwegian glacier
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by integrating computational mental health and computational social science, using large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns
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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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Sustainable Fibre Sources (fibrematch.eu), funded by the European Innovation Council (EIC). The project aims to match dietary fibre types to prevalent functional gut microbiome subtypes to increase fibre
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interdisciplinary work combines advanced computational tools, including 4D point cloud modeling and state-of-the-art machine learning and deep learning techniques (such as generative adversarial networks), with
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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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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