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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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associations with socio-economic markers, health, gut microbiomes, and antibiotic resistance in large population cohorts and big data to help mitigate the global antimicrobial resistance (AMR) crisis. AMR is one
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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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. 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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variability and the predictability of mechanistic CH4 models. We aim to fill the knowledge gap in the project “A holistic view of Methane turnover in northern Wetlands by Novel isotopic approach (MeWeN
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a dynamic, international research environment. Your experience and ambitions Required Qualifications PhD in Electrical Engineering, Physics, Photonics, Materials Science, or related field Strong
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information, visit the lab web pages: See also our recent publication: DOI: 10.1038/s41467-024-54445-1 Your qualifications We are looking for ambitious researchers with a PhD, a solid publication record, and
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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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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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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