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, metabolism and microbiota. Our methodological approaches include cell cultures, animal models and randomised controlled trials. Responsibilities and qualifications We are looking for a motivated postdoctoral
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of Advanced Mathematics for Sensing, Imaging and Modelling (2024–2031). The group is also supported by a Research Council of Finland Fellowship under the project SPARSe (2025–2029), further strengthening its
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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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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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on health and prevention of non-communicable diseases. Our main focus is on gut physiology, metabolism and microbiota. Our methodological approaches include cell cultures, animal models and randomised
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models using sophisticate genetic tools, in vivo time-lapse imaging and multi-omics methods to decipher the underpinning mechanisms of regeneration. Our findings provide new targetable mechanisms
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developed will be based on pseudonymization, anonymization, and synthetic data generation. Using real health data as a source of information, we aim to create test datasets and statistical models
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computing in large-scale omics data analysis. Your work will focus on method development and their application to biomedical research questions. Key responsibilities include: analyzing and modeling large