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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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parental leave usage across different population groups and how the use of leave has changed over time and in various social environments: workplaces, residential areas, and extended family networks
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protons are present and accelerated, or an admixture of the two. The composition affects the power of the jet and the presence or lack of hadrons is a crucial ingredient in modelling the multi-wavelength
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(FIMM) , University of Helsinki, is currently seeking a highly-motivated postdoctoral researcher to join our interdisciplinary team. Project overview This project aims to develop machine learning models
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. Integrate environmental, spatial, and social data into digital twin models for scenario testing and policy simulation. Adapt co-design methods to local contexts in demonstrator sites (Portugal, Sweden, Italy
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air quality modelling. The project is funded by the Jane and Aatos Erkko Foundation. Research tasks include Developing future emission scenarios for various urban environments; Updating and applying
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, automated reaction mechanism generators, and high-resolution local scale air quality modelling. The project is funded by the Jane and Aatos Erkko Foundation. Research tasks include Developing future emission
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mental health and computational social science, using large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data
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metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
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project CONFSTAT – Conformally invariant and near critical models in statistical field theory. The work of the postdoctoral researcher will focus on studying conformally invariant models of statistical