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models of cancer outcomes and treatment resistance. For more information, visit kuijjerlab.org . The advertised project focuses on extending a deep learning framework, originally developed by the Kuijjer
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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with
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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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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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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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. To solve this, the HiFi-MuTaNTS project, which is a consortium between the Geological Survey of Finland (GTK), University of Helsinki, and CSC – IT Center for Science, proposes a model-based scientific
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using unique novel mouse models, spatial technologies and analytical methods. Postdoctoral Researcher in Functional Cancer Microbiome through the NORPOD program NORPOD is a collaborative postdoctoral
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agent-based modeling or another relevant computational approach for the simulation of managed retreat. We look for a candidate in sustainability or environmental social sciences or a related field who
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metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
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Cancer Medicine at the Faculty of Medicine, University of Helsinki. The project will focus on developing approaches for gene regulatory network modeling on deconvoluted bulk data, with applications to pan