Qualifications

Applicants should have a master’s degree or higher in bioinformatics, computational biology or biomedical data science. The ideal candidate should have strong science communication skills; clear and effective data visualization skills; the ability to work well independently and in a team environment; creative problem-solving skills; and a proven ability to apply the cutting-edge, rigorous standards of the bioinformatics fields. Applicants should possess a solid knowledge of R statistical programming language; familiarity with the handling, management and storage of large-scale sequencing data; and experience querying public databases, including the SRA, GEO and dbGaP.

Preferred qualifications include experience with next-generation sequencing methods on Illumina and 10x Genomics platforms (e.g., bulk and single-cell RNA-Seq; ChIP-seq methods, such as MeDIP-seq; bulk and single-cell ATAC-seq; and miRNA-seq). Experience with other ‑omics — such as WES, WGS and targeted sequencing methods — are a plus. The ideal candidate will have experience with preprocessing tools for alignment, counting or sequence analysis (e.g., Cell Ranger, STAR, HTSeq, featureCounts, salmon, GATK) and R packages designed for the above-mentioned methods (e.g., DESeq2, limma, Seurat). A solid understanding of clustering and dimensionality reduction techniques for big genomic datasets, experience with Python programming, and familiarity with Linux BASH scripting, which is necessary for proper utilization of NIH’s high-performance computing capabilities, are preferred.