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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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. 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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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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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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immune-system related diseases such as immunodeficiency and cancer. We use a wide range of techniques such as mouse models, tumor models, in vivo immune cell migration and other functional assays, flow
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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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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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-Gordon model, the scaling limit of the near critical Ising model, or the massive Thirring model. Qualifications We are looking for applicants with a PhD in mathematics or theoretical physics, with
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facilities with access to the state-of-the art technologies. Qualifications We invite applications from candidates with a solid theoretical and wet-lab background and a PhD degree in cell/molecular biology
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to contribute to the preparation of funding applications, supervise/mentor MSc and PhD students and contribute to teaching activities. Requirements We look for candidates in the field of sustainability assessment