Computational Scientist II, CGR, NCI Sherlock-Lung

This position supports the Cancer Genomics Research Laboratory at the National Cancer Institute, collaborating with the Division of Cancer Epidemiology and Genetics. The role focuses on advancing the Sherlock-Lung Study, examining genomic and transcriptomic landscapes in lung cancer among never-smokers across 3,000+ subjects.

Key Responsibilities

• Formulate and test hypotheses regarding mutational processes and tumor evolution in lung cancer
• Lead integrative analyses of somatic variation, mutational signatures, and driver events using whole-genome sequencing and multi-omics datasets
• Apply statistical approaches to extract insights from large genomic datasets
• Evaluate and implement emerging analytical methods for single-cell and spatial analyses
• Ensure reproducibility and scalability of computational workflows
• Lead peer-reviewed publications and present findings at scientific meetings
• Contribute to study design and analytical strategy

Basic Requirements

• PhD from accredited institution
• Minimum 2 years progressively responsible experience
• Demonstrated expertise in tumor genomics and cancer biology
• Proficiency with NGS data analysis, somatic whole-genome sequencing, and multi-omics integration
• Strong statistical and machine learning skills for high-dimensional genomic data
• Experience with genomic databases (TCGA, gnomAD, UK Biobank, etc.)
• Proficiency in Bash, R, Python, RStudio, and GitHub
• Significant HPC and SLURM experience
• Track record of peer-reviewed publications
• Ability to obtain security clearance

Preferred Qualifications

• 5+ years postdoctoral or equivalent experience
• Expertise in lung cancer biology
• Advanced tumor genomic analyses (driver identification, mutational signatures, copy number phasing)
• Multi-omic integration experience
• Familiarity with Docker, Singularity, Snakemake, or Nextflow