16 combustion-modelling-postdoc Postdoctoral positions at UNIVERSITY OF HELSINKI in Finland
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methodology for analysing long-term spatially structured data sets within a joint species distribution modelling framework. For more information on REC, please see https://www2.helsinki.fi/en/researchgroups
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distribution modelling framework. For more information on REC, please see https://www2.helsinki.fi/en/researchgroups/research-centre-for-ecological-change/ A POSTDOCTORAL RESEARCHER POSITION IN BIODIVERSITY
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air quality modelling. The project is funded by the Jane and Aatos Erkko Foundation. Research tasks include Developing future emission scenarios for various urban environments; Updating and applying
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, automated reaction mechanism generators, and high-resolution local scale air quality modelling. The project is funded by the Jane and Aatos Erkko Foundation. Research tasks include Developing future emission
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project CONFSTAT – Conformally invariant and near critical models in statistical field theory. The work of the postdoctoral researcher will focus on studying conformally invariant models of statistical
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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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, 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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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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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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(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