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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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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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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
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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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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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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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2025, or as agreed, in a fixed-term contract until 31.8.2029. Background The positions are opened in the HIP CMS experiment group, which contributes to the analysis of data from the CERN CMS experiment
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of the near critical Ising model, or the massive Thirring model. Qualifications We are looking for applicants with a PhD in mathematics or theoretical physics, with experience in mathematically rigorous