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, or representation learning. Experience analysing large-scale single-cell omics data. Experience with integrative multi-omics data, such as genomics, proteomics, or metabolomics. Experience with relevant machine
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, or representation learning. Experience analysing large-scale single-cell omics data. Experience with integrative multi-omics data, such as genomics, proteomics, or metabolomics. Experience with relevant machine
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a research staff of 180, of which 65 are PhD students. More information about us, please visit Department of Molecular Biosciences, The Wenner-Gren Institute Project description Proteomics-driven
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mesocosm and field experiments. Analytical work will be done in close collaboration with the Umeå Proteomics Platform. https://www.umu.se/en/research/infrastructure/umea-proteomics-platform/ The project is
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interest in innate immunity, infection biology and proteomics. The position at the Department of Molecular Biology at Umeå University is temporary for four years to start in October 2026 or as agreed
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health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive dynamical models and digital decision-support tools for nutrition and health method development in
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The project aims to develop large-scale self-supervised models trained on rich, longitudinal health data, including: Medical records Lifestyle data Biological samples (genomics, transcriptomics, proteomics, etc
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, proteomics, long-read sequencing). Familiarity with machine learning approaches, particularly artificial neural networks, and their application to biological data. Experience with workflow management systems