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for large-scale pan-cancer multiomics data. We build on our previous work (e.g., Sanjaya et al. Genome Medicine 2023 ; Pohjonen et al. arXiv 2024 ), developing the new models on the LUMI supercomputer and
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responsible for the teaching and research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data
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of gene regulatory networks in various cell types. The research will leverage a large in-house dataset from iCAN, complemented by publicly available data. These efforts aim to uncover in more detail
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for an expert in quantitative methods and data analytics. The position involves designing and conducting research utilizing regional big data. The primary task is to develop the field of regional data analytics
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the modeling of both shared and data type-specific variability. By doing so, it provides insights into the regulatory mechanisms underlying cancer. The research will leverage a large in-house dataset from iCAN
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for an expert in quantitative methods and data analytics. The position involves designing and conducting research utilizing regional big data. The primary task is to develop the field of regional data analytics
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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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students. The Department of Physics (Faculty of Science ) is a large and multidisciplinary department that offers the most varied university programme in the physical sciences in Finland. At the beginning
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not essential for the application. Have experience in: (i) creating and maintaining optimal data pipeline architecture; (ii) assembling large, complex data set and set up annotation tools; (iii
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R, algorithms and systems designed to extract insights from large datasets. Experience with integrating and analyzing diverse data sources, such as biodiversity (e.g., the IUCN Red List of Species and