Computational Scientist II, CGR, NCI Sherlock-Lung

About the role

The Frederick National Laboratory is operated by Leidos Biomedical Research, Inc. The lab addresses some of the most urgent and intractable problems in the biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, applications of nanotechnology in medicine, and rapid response to emerging threats of infectious diseases.

Responsibilities

• Formulate and test biological hypotheses related to mutational processes, intra-tumor heterogeneity, clonal architecture, and evolutionary dynamics in lung cancer.
• Lead integrative analyses of somatic and germline variation (SNVs, indels, structural variants, copy number alterations), mutational signatures, and driver events using large-scale short-read and long-read WGS and multi-omics datasets.
• Apply advanced statistical approaches to extract insights from genomic datasets and synthesize findings with clinical and multi-omics data.
• Critically evaluate and implement emerging analytical methods for single-cell, spatial, and multi-omics analyses to enhance biological discovery.
• Ensure analytical rigor, reproducibility, and scalability of computational workflows.
• Lead and contribute to peer-reviewed publications, present findings at scientific meetings, and communicate results to multidisciplinary collaborators.
• Contribute to study design and analytic strategy for ongoing and future Sherlock-Lung initiatives.

Requirements

• Possession of a PhD degree from an accredited college or university according to the Council for Higher Education Accreditation (CHEA). Foreign degrees must be evaluated for U.S. equivalency.
• A minimum of two (2) years of progressively responsible experience.
• Demonstrated experience and in-depth understanding of tumor genomics and cancer biology.
• Proven expertise in next-generation sequencing (NGS) data analysis and visualization using both custom and open-source bioinformatics tools, with a focus on somatic whole-genome sequencing analyses and multi-omics data integration.
• Proficiency with core statistical methods and modern machine learning approaches appropriate for high-dimensional genomic data, with emphasis on biological interpretability.
• Significant experience with high-performance computing (HPC) environments and job scheduling systems such as SLURM.
• Extensive proficiency in scripting and programming languages including Bash, R, and Python, with experience in RStudio, Jupyter Notebooks, and code management on GitHub.
• Proven experience preparing high-impact research manuscripts for peer-reviewed publications.
• Ability to obtain and maintain a security clearance.

Qualifications

• Minimum of five years of postdoctoral or equivalent experience in academia or industry.
• Strong written, verbal, and presentation skills. Ability to work effectively in a multidisciplinary research environment and communicate technical findings clearly to non-specialist audiences.
• Biological expertise in lung cancer with the ability to lead and drive large-scale projects.
• Hands-on experience with advanced tumor genomic analyses such as driver gene identification, mutational signature deconvolution, copy number phasing, tumor purity, microsatellite instability detection, and telomere length estimation.
• Expertise in integrative multi-omic analyses, including genomics, transcriptomics, epigenomics, and emerging spatial/single-cell modalities.
• Strong understanding of algorithmic efficiency and experience working in HPC and cloud environments to analyze population-scale datasets.
• Experience with various environment/dependency management tools (e.g. pip, venv, conda, renv), containerization with Docker/Singularity, and workflow management systems such as Snakemake or Nextflow.
• Proven ability to work both independently and collaboratively as part of a team.

Benefits

• Competitive compensation
• Health and Wellness programs
• Income Protection
• Paid Leave
• Roth 401(k)
• Retirement

Pay and Benefits

The posted pay range for this job is a general guideline and not a guarantee of compensation or salary. Additional factors considered in extending an offer include, but are not limited to, responsibilities of the job, education, experience, knowledge, skills, and abilities as well as internal equity, and alignment with market data.

Contact

To apply, visit www.frederick.cancer.gov.