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sequencing platforms (e.g. NextSeq 2000, NovaSeq X Plus). The role also includes continuous improvement and standardization of existing analysis methods (e.g. single-cell applications, basic histology and
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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individual laboratories. Computational methods and artificial intelligence based on large-scale molecular data are transforming the study of biological systems at all levels – from molecular structures and
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providers across the country to perform advanced genome and transcriptome analyses based on large-scale DNA sequencing, while also continuously developing methods and pipelines. Our goal is to ensure world
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fellow in data-driven cell and molecular biology. For more information about us, please visit: DBB and MBW Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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. Project description: DDLS Fellows Program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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haplogroups, principal component analysis, analysis, analysis of kinship, trait analysis and metagenomic analysis (incl. analysis of pathogenic microorganisms). The bioinformatician is involved in maintaining
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. With cutting-edge research, top-tier education, and extensive collaborations, we are a key force in the field. Our core competencies include in vitro ADME models, advanced in vivo methods, computational
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methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and
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infrastructure and research community, bringing together groundbreaking life science technologies with data and AI expertise. Computational methods and artificial intelligence applied to large-scale molecular data