The candidate is responsible for analyzing and mining multi-omics data using computational techniques, such as deep learning, generalized linear mixed models, and biological network analysis. This may require development of new computer algorithms and/or construction of computational workflows on computer clusters. The types of multi-omics data will include longitudinal metagenomics sequencing data, genome-wide association (GWAS) data, proteomics data, and metabolomics data. The candidate is expected to publish their findings in peer-reviewed journals
Requirements:
Ph.D; Skills in Bioinformatics, deep learning, data science, -omics
Text:
Postdoctoral Researcher in Bioinformatics & Computational Biology The candidate is responsible for analyzing and mining multi-omics data using computational techniques, such as deep learning, generalized linear mixed models, and biological network analysis. This may require development of new computer algorithms and/or construction of computational workflows on computer clusters. The types of multi-omics data will include longitudinal metagenomics sequencing data, genome-wide association (GWAS) data, proteomics data, and metabolomics data. The candidate is expected to publish their findings in peer-reviewed journals Ph.D. Skills in Bioinformatics, deep learning, data science, -omics
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