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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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responsibilities Design, implement and benchmark deep machine learning models for large-scale cancer datasets that include genomics, transcriptomics, epigenomics and imaging data Collaborate closely with
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, normalization, dimensionality reduction) to downstream interpretation (differential expression, gene set enrichment, and cell type annotation). Implement Machine Learning Approaches, including deep learning
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separation technologies from different points of view. The work requires deep scientific understanding of the related physical and chemical phenomena, exploration and development of novel and existing
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the Department of Computer Science, and the person is expected to engage in deep collaboration with research groups at Faculty of Science and Faculty of Pharmacy to enhance cutting edge research in the area. The
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expected to engage in deep collaboration with research groups at Faculty of Science and Faculty of Pharmacy to enhance cutting edge research in the area. The focus of the position is on application and