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samples which are complemented by DNA methylation, DNA and RNA sequencing as well as clinical data. Together with the Artificial Intelligence and Cancer Evolution Division at the German Cancer Research
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epidemiologic methods for environmental ‘omics and related software packages, including R, SAS, Python or equivalent. Previous experience analyzing large DNA methylation datasets, bioinformatics, and use
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epidemiologic and biostatistical training and be proficient with R-statistical software. Prior experience with single omics data and multi-omics integration (e.g., DNA methylation, transcriptomics, proteomics
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term environmental changes. When environmental change is rapid, however, genetic variation may be insufficient on its own. Another layer of variation is the epigenome, e.g. DNA methylation (DNAme), which
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also collaborating with researchers in other domains for data analytics and decision making. Liu lab has access to rich high-dimensional multi-omics data, including WGS, WES, DNA methylation, RNA-seq