Genomics & Epigenomics Analyst – Long-Read Sequencing

GAP Solutions Inc; Baltimore (MD); On-site; USD 65,000 - 90,000; Full time

Job summary

GAP Solutions Inc. is seeking a laboratory and computational analyst to support NIH/NIA genomic and epigenomic data analysis. The role involves genotyping, long-range sequencing, and DNA methylation profiling using established protocols and QC pipelines.

The ideal candidate holds a Master’s degree in biology or a related field, has 2+ years of hands-on experience in R and scripting, and can document methods and results clearly for NIH collaboration.

Qualifications

• Master's degree in biology or related field.
• At least 2 years of experience.
• Proficiency in R and at least one scripting language.
• Experience with QC and data visualization.
• Familiarity with genomic data formats (FASTQ, BAM, VCF).

Responsibilities

• Evaluate read quality, coverage, depth, and sample integrity.
• Flag anomalies and provide preliminary interpretation.
• Perform DNA extraction from blood, tissue, or cultured cells.
• Conduct genotyping assays (e.g., SNP arrays, PCR-based methods).
• Support long-range sequencing workflows (library prep and sequencing).
• Perform DNA methylation assays (bisulfite conversion, array-based or sequencing-based).
• Execute QC pipelines for sequencing and genotyping data.
• Document QC metrics in standardized formats.
• Modify scripts and pipelines to support project needs.
• Analyze data using R and scripting languages (Python, Bash).
• Prepare summary tables and figures; write methods and results sections.

Skills

R

Scripting language (Python/Bash)

Education

Master's degree in biology

Tools

QC pipelines

Data visualization tools

Job description

GAP Solutions Inc. is seeking a laboratory and computational analyst to support NIH/NIA genomic and epigenomic data analysis. The role involves genotyping, long-range sequencing, and DNA methylation profiling using established protocols and QC pipelines.

The ideal candidate holds a Master’s degree in biology or a related field, has 2+ years of hands-on experience in R and scripting, and can document methods and results clearly for NIH collaboration.