Biologist (Genomics) (50865)

Open 29d

Position Objective: The National Institutes of Health requires contractor support for laboratory and computational analysis of genomic and epigenomic data. The work supports ongoing research involving genotyping, long-range sequencing, and DNA methylation profiling at the National Institute on Aging (NIA) within the National Institutes of Health (NIH).

Duties and Responsibilities:

  • Evaluate: Read quality, coverage, and depth and Sample integrity and contamination
  • Flag anomalies and provide preliminary interpretation.
  • Perform DNA extraction from blood, tissue, or cultured cells using established protocols. 1
  • Conduct genotyping assays (e.g., SNP arrays, PCR-based methods 2
  • Support long-range sequencing workflows (e.g., library prep and sequencing using long-read platforms such as PacBio or Oxford Nanopore). 3
  • Perform DNA methylation assays (e.g., bisulfite conversion, array-based or sequencing-based methods).
  • Execute established QC pipelines for sequencing and genotyping data.
  • Compile and document QC metrics in standardized formats.
  • Modify existing scripts and pipelines to support project needs.
  • Perform data analysis using: R (statistical analysis and visualization) and Scripting (Python, Bash, or equivalent)
  • Conduct: Variant calling and basic annotation and DNA methylation data processing and analysis and Data integration across datasets when directed
  • Maintain accurate laboratory notebooks and electronic records.
  • Identify routine technical issues and implement standard troubleshooting steps.
  • Prepare: Summary tables and figures and Written summaries of methods and results
  • Present findings in internal meetings to NIH staff
  • Contribute to draft reports, manuscripts, or project updates.
  • Sample Processing Logs DNA extraction records and yields
  • Genotyping/Sequencing Outputs Raw and processed data files
  • QC Reports Standardized quality metrics and summaries
  • Analysis Outputs Variant and methylation results, visualizations
  • Scripts and Code Documented R/Python/Bash scripts
  • Monthly Summary of work performed and findings
  • Presentation Materials Slides or briefings for NIH staff