Post Doctoral Research Scholar
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This is a one-year post-doctoral appointment (with possible renewal) to provide advance research training to individuals with a doctoral degree in biological or computational sciences and to further the basic and translational research goals at the Children's Research Institute.
The next frontier in human genomics explores its tissue specific function and the impact of the environment on the genome. Genome-wide association studies (GWAS) have been successful in identifying hundreds of common genetic variants associated with various traits. In general, as most GWAS loci map preferentially to non-coding DNA, only few have been translated to pathogenetic mechanisms. Likewise, environmental epigenetic variants associated with disease risk have similar feature mapping to distal tissue-specific regulatory elements (enhancers) but where majority of target genes are unknown. We seek a highly motivated, team-oriented individual with good organizational, interpersonal, and communications skills to tackle challenges in next-generation epigenomics within a dynamic multi-disciplinary environment. The successful candidate will be working on filling these gaps and identify target genes and mechanisms affected by epigenetic modulations. The program will use multiple approaches in a variety of human disease-targeted primary cell models and tissue cohorts as well as animal models. Specifically, the successful candidate will be responsible for the analysis of functional genomics and epigenomics data including RNA-Seq, DNA methylation, ChIP-Seq, ATAC-Seq and single-cell (10x genomics) data. The position is based at the Center for Pediatric Genomic Medicine where successful candidates will have access to state-of-the-art core facilities including computational cluster resources.
PhD or MD or related doctoral level degree in a relevant discipline
1 year experience
Experience in application of statistical methods to the analysis of large-scale genetic/genomics data
A firm grounding in statistical and computational methods relevant to the analysis of NGS data
Preferable knowledge of other relevant subjects related to the project including single-cell analysis