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the entire population. The project utilises advanced statistical methods such as multilevel models (mixed models), fixed-effects models, cluster analysis, and sequence analysis. The selected researcher is
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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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(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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, programming, Linux, data, and infrastructure perspective: short-term projects helping researchers with specific tasks, so that the researchers gain competence to work independently. Provide good role models
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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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strong background in any of the following: preclinical models, vascular/cancer biology, or cell biology. Applicants should be comfortable working both independently and as part of a team, with strong
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using unique novel mouse models, spatial technologies and analytical methods. Postdoctoral Researcher in Functional Cancer Microbiome through the NORPOD program NORPOD is a collaborative postdoctoral
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applications. Addressing food and nutritional security requires novel ways of producing sustainable, safe, affordable, healthy and flavourful food. Europe alone faces numerous challenges related to the rise in
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agent-based modeling or another relevant computational approach for the simulation of managed retreat. We look for a candidate in sustainability or environmental social sciences or a related field who
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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