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at the Faculty of Medicine, University of Helsinki. The project will focus on using and extending deep learning-based approaches developed within the group to integrate bulk multi-omics cancer data. The Kuijjer
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methods to understand the regulatory mechanisms driving cancer heterogeneity and progression by integrating genomic data into genome-wide regulatory networks. Current projects include (i) modeling distal
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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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on Research Integrity (TENK) 3/2020 CV template (https://www.tenk.fi/en/template-researchers-curriculum-vitae ) Numbered list of publications following the Research Council of Finland format (https://www.aka.fi
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on Research Integrity (TENK) 3/2020 CV template (https://www.tenk.fi/en/template-researchers-curriculum-vitae ) Numbered list of publications following the Research Council of Finland format (https://www.aka.fi
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and analyses that can help investigate human-nature interactions to inform decision making. We carry out global to local analyses, by integrating traditional and novel digital data sources. Our research
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2 diabetes, and cancers. In close collaboration with multidisciplinary researchers, we integrate biobank resources, clinical data, omics technologies, as well as novel computational approaches
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the dual nature of hope towards technology in sustainability transitions through an interdisciplinary approach that combines empirical and conceptual research. The project integrates science and technology
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ships, assuming a static operative environment. These approaches also fail to integrate stakeholder feedback, thereby limiting their practical applicability. To address these gaps, you will develop
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an idea on how to contribute to the HI research theme. CV, following the guidelines of the Finnish Advisory Board on Research Integrity List of publications, following the guidelines of the Academy