Job Description

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.

Accountability, Compassion, Collaboration, Dedication, Integrity and Versatility; it’s the FNL way.

PROGRAM DESCRIPTION

We are seeking a skilled and motivated Computational Scientist II to join the Cancer Genomics Research Laboratory (CGR), located at the National Cancer Institute (NCI) Shady Grove campus in Rockville, MD (actual work location negotiable). CGR is operated by Leidos Biomedical Research, Inc., and collaborates with the NCI’s Division of Cancer Epidemiology and Genetics (DCEG) – the world’s leading cancer epidemiology research group. Our scientific team leverages cutting-edge technologies to investigate genetic, epigenetic, transcriptomic, proteomic, and molecular factors that drive cancer susceptibility and outcomes. We are deeply committed to the mission of discovering the causes of cancer and advancing new prevention strategies through our contributions to DCEG’s pioneering research.

Our team of CGR bioinformaticians supports DCEG’s multidisciplinary family- and population-based studies by working closely with epidemiologists, biostatisticians, and basic research scientists in DCEG’s intramural research program. We provide end-to-end bioinformatics support for genome-wide association studies (GWAS), methylation profiling, targeted, whole-exome, whole-transcriptome and whole-genome sequencing along with viral and metagenomic studies from both short- and long-read sequencing platforms. Our work spans germline and somatic variant detection, structural and copy number variation, microsatellite analysis, mutational signature profiling, gene and isoform expression, base modification analysis, viral and bacterial genomics, and more.  Additionally, we advance cancer research by integrating latest technologies such as single-cell and spatial transcriptomics, multiomics and proteomics, in collaboration with the Functional and Molecular and Digital Pathology Laboratory groups within CGR. We extensively analyze large population databases such as All of Us, UK Biobank, gnomAD and 1000 Genomes to inform and validate GWAS signals, study the association between genetic variation and gene expression, protein levels, and metabolites and to develop polygenic risk scores across multiple populations.

Our bioinformatics team develops and implements sophisticated, cloud-enabled pipelines and data analysis methodologies, blending traditional bioinformatics and statistical approaches with cutting-edge techniques like machine learning, deep learning, and generative AI. We prioritize reproducibility through containerization, workflow management tools, thorough benchmarking, and detailed workflow documentation. Our infrastructure and data management team works closely with researchers and bioinformaticians to maintain and optimize a high-performance computing (HPC) cluster, provision cloud environments, and curate and share large datasets.

The successful candidate will provide dedicated scientific and analytical support to the Integrative Tumor Epidemiology Branch (ITEB) through their expertise in tumor genomics, lung cancer biology, and epidemiology. They will advance the Sherlock-Lung Study, a large-scale initiative investigating the genomic, transcriptomic, and methylation landscapes of lung cancer in never smokers, as well as their spatial architecture, to uncover mutational processes, molecular changes, and tumor evolution.

The Computational Scientist II will lead integrative analyses and scientific interpretation of somatic high-coverage whole-genome sequencing (WGS) and multi-omics datasets from the Sherlock-Lung cohort, consisting of over 3,000 subjects. This position centers on hypothesis-driven investigation that combines biological and computational expertise, with leadership in producing high-impact publications that advance understanding of lung cancer development and progression.

KEY ROLES/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.

BASIC QUALIFICATIONS

To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:

• 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.
• In addition to the education requirement, 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.
• Strong experience working with genomic databases such as TCGA, dbGaP, gnomAD, cBioPortal, ENCODE, 1000 Genomes, All of Us, GTEx, ICGC, PCAWG, and UK Biobank.
• Extensive proficiency in scripting and programming languages including Bash, R, and Python, with experience in RStudio, Jupyter Notebooks, and code management on GitHub.
• Significant experience with high-performance computing (HPC) environments and job scheduling systems such as SLURM.
• Proven experience preparing high-impact research manuscripts for peer-reviewed publications.
• Ability to obtain and maintain a security clearance.

PREFERRED QUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

• 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.

Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, color, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.

Pay and Benefits

Pay and benefits are fundamental to any career decision. That’s why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available here

124,800.00 – 178,797.00 USD

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.

The salary range posted is a full-time equivalent salary and will vary depending on scheduled hours for part time positions