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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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, 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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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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, 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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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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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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stimulation) to be used in animal model experiments. The work is based on previous development on materials, devices and cell experiments within this project and it is supported by the whole multidisciplinary
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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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Researcher will strengthen the group’s work on developing a transnational comparative model. A potential focus of their research either on the so-called ‘second-world’ literatures or the European literary
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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