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-cancer data network analysis. The Kuijjer group, established in 2018 at the University of Oslo, has recently expanded to the University of Helsinki. The group specializes in developing computational
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. We require the candidate to have documented experience in either large-scale genomics data analysis with computational or approaches/biostatistics, or machine learning/deep learning. Experience with
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their impact on gene function and structure using a range of sequence analysis and comparative genomic methods. The projects will also involve programming for data collection and analysis. As a
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(DGL) at the University of Helsinki. Selection criteria We are looking for a candidate with expertise in quantitative big data analysis and a strong interest in developing regional data analytics methods
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in these diseases. The postdoctoral fellows will work on computational method development and data analysis for bulk and single-cell omics data from human patient samples. Individuals with a strong
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(DGL) at the University of Helsinki. Selection criteria We are looking for a candidate with expertise in quantitative big data analysis and a strong interest in developing regional data analytics methods
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should hold a PhD degree in molecular biology, biochemistry, cancer biology or related fields. Expertise in biochemistry, transcriptomics, NGS data analysis and basic programming in R/Python is a pre
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advanced computational tools to dissect the role of alternative splicing in these diseases. The postdoctoral fellows will work on computational method development and data analysis for bulk and single-cell
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(v) creating data tools for analysis and scientific requirements in the team. Be willing to work in an interdisciplinary team, carrying out research in conservation science that can help address