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Association Studies (GWAS). GWAS test hundreds of thousands of genetic variants across many genomes to find those statistically associated with a specific trait or disease, which is computationally very
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implementation (using common frameworks as Pytorch, TensorFlow, etc.); Proficiency with common programming languages (e.g., Python, Java, C++); Knowledge of (geo)statistics and of geospatial data processing
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Science or in a related field · Knowledge of programming languages such as R and Phyton and statistical methods applied to biosciences · Proven ability to analyze next-generation sequencing data such as RNA
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should have expertise in statistics, programming, and the analysis of cancer omics data. Interest in network biology and knowledge of data science techniques such as machine learning and being familiar
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data (maximum 20 points); Approaches for the statistical modelling of microbiomes, including meta-analytical and machine-learning methods (maximum 20 points); Computational methods for functional