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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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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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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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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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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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funded by the ERC consolidator grant project CONFSTAT – Conformally invariant and near critical models in statistical field theory. The work of the postdoctoral researcher will focus on studying
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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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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