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-driven working culture. The research activities are carried out in research groups joined into three multidisciplinary research programs. For more information, please visit https://www.helsinki.fi/hilife
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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
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driving cancer heterogeneity and progression by integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal regulatory interactions, (ii) modeling networks
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and curiosity-driven working culture. Research activities are carried out in research groups organised into three multidisciplinary research programmes. For further information please visit https
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author) in the field of computational biophysics (molecular dynamics simulations and/or quantum chemistry). Any experience in development and application of AI/ML methods in tandem with modeling and
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to: Develop and apply machine learning models for analyzing complex datasets related to nature conservation. Establish and maintain code and data repositories to ensure efficient workflow and collaboration
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research We conduct data-driven research to understand the pathogenesis of human diseases, with a focus on metabolic disorders, such as obesity, metabolic dysfunction-associated steatotic liver disease, type
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for extension through application for further funding by the applicant and PI. Our research We conduct data-driven research to understand the pathogenesis of human diseases, with a focus on metabolic disorders
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-requisite for the position. Previous experience of working with in vivo models of cancer is considered an advantage. Strong command in written and spoken English is required. The chosen applicant is expected
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significant merit: (mammalian) cell culturing techniques, in vivo models, high throughput screening, molecular biology or bioinformatics excellent written and verbal communication skills (in English) strong