Senior Bioinformatician - NCI/ ITEB

Senior Bioinformatician - NCI/ ITEB

Job ID: req4424
Employee Type: exempt full-time
Division: Clinical Research Directorate
Facility: Rockville: 9609 MedCtrDr
Location: 9609 Medical Center Dr, Rockville, MD 20850 USA

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 Bioinformatics Analyst to join the Cancer Genomics Research Laboratory (CGR), located at the National Cancer Institute (NCI) Shady Grove campus in Rockville, MD. 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 analytical support to the Integrative Tumor Epidemiology Branch (ITEB) and contribute to cancer research through their expertise in DNA repair, lung cancer, epidemiology, and cancer genetics to advance the Sherlock-Lung Study, a large-scale initiative investigating the genomic, transcriptomic, methylation, and microbiome landscapes of lung cancer in never smokers to uncover mutational processes, molecular changes, and tumor evolution.

The Bioinformatics Analyst IV will analyze and integrate somatic and germline deep whole-genome and multi-omics datasets from the Sherlock-Lung cohort, consisting of over 3,000 subjects, ensuring timely progress toward key scientific milestones and publications. This role involves analyzing large-scale sequencing data, developing and maintaining robust pipelines, performing downstream statistical modeling, generating high-quality visualizations and interpreting results for data summarization and interpretation and manuscript preparation. The candidate will be expected to:

KEY ROLES/RESPONSIBILITIES

• Formulate hypotheses for large-scale cancer studies and test them by analyzing single nucleotide variants (SNVs), indels, structural variants (SVs), copy number alterations (SCNAs), clonal and subclonal drivers, and mutation signatures to characterize intra-tumor heterogeneity, with a particular focus on lung cancer.
• Develop, implement, and optimize pipelines for somatic variant analysis from short- and long-read WGS, including:
  • Raw data processing, alignment, and quality control.
  • Tumor purity estimation.
  • Somatic mutation calling (SNVs, indels, SVs, CNAs) using best-practice workflows.
  • Advanced analyses such as driver gene identification, mutational signature deconvolution, microsatellite instability detection, telomere length estimation, and Battenberg copy number phasing.
• Apply statistical methods to interpret genomic datasets and integrate findings with clinical and multi-omics data.
• Research, evaluate, and implement state-of-the-art computational methods for single-cell, multi-omics, and spatial omics analyses, and communicate findings to diverse audiences.
• Maintain and document pipelines, software, and scripts to ensure reproducibility and scalability.
• Provide support for analysis of genomic data from epidemiological studies. This includes but is not limited to data manipulation, and integrated genomic analyses. Prepare various reports and presentations detailing the methodology and results.
• Present findings at meetings and lead/contribute to peer-reviewed publications.

BASIC QUALIFICATIONS

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

• Possession of Master’s degree from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) or four (4) years relevant experience in lieu of degree. Foreign degrees must be evaluated for U.S. equivalency.
• In addition to the education requirement, a minimum of ten (10) years of progressively responsible experience.
• Proven expertise in next-generation sequencing (NGS) data analysis, with a focus on somatic whole-genome sequencing analyses and multi-omics data integration.
• Demonstrated experience with custom and open-source pipelines for large-scale data analysis.
• Demonstrated experience and in-depth understanding of lung cancer biology and cancer genomics, with a strong track record in result interpretation and summarization of findings for publications.
• Expert-level knowledge of bioinformatics tools for primary and secondary NGS data processing for large cancer datasets, statistical modeling, phenotype/genotype integration and visualization.
• Strong experience using genomic databases such as TCGA, dbGAP, gnomAD, cBioPortal, ENCODE, 1000 Genomes, AllofUs, GTEx, ICGC, PCAWG and UK Biobank.
• Extensive proficiency in scripting and programming languages including Bash, R and Python with experience in RStudio and Jupyter Notebooks, managing code 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:

• Strong written, verbal, and presentation skills. Ability to work effectively in a multidisciplinary research environment and communicate technical findings clearly to non-specialist audiences.
• Self-motivated, research-focused professional with a passion for advancing cancer genomics.
• Demonstrated scientific contributions through a strong publication record in high-impact journals.
• Proficiency with core statistical, machine learning and bioinformatics analytical methods.
• Strong experience with large-scale multi-omics data integration (e.g., genomics, genetics, transcriptomics, DNA methylation, etc.).
• Strong understanding of algorithmic efficiency and working on high performance clusters for supporting large and diverse datasets.
• Experience with various environment/dependency management tools (e.g. pip, venv, conda, renv) and workflow management systems such as Snakemake or Nextflow.
• Knowledge of containerization with Docker/Singularity, JIRA and GitHub for project management.
• Strong analytical and problem-solving skills with attention to detail.
• Strong communication skills, and the ability to work both independently and collaboratively as part of 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

123,800.00 - 207,125.00 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