Bioinformatics, Analyst II - ITEB, CGR

Bioinformatics, Analyst II - ITEB, CGR

Job ID: req4277
Employee Type: exempt full-time
Division: Clinical Research Program
Facility: Rockville: 9615 MedCtrDr
Location: 9615 Medical Center Drive, 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 professional 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, targeted, whole-exome, whole-transcriptome and whole-genome sequencing along with viral and metagenomic studies from both short- and long-read sequencing platforms. This includes the analysis of germline and somatic variants, structural variations, copy number variations, gene and isoform expression, base modifications, viral and bacterial genomics, and more. Additionally, we advance cancer research by integrating latest technologies such as single cell, multiomics, spatial transcriptomics, 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 and 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 models. We prioritize reproducibility through the use of 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 incumbent will provide dedicated analytical support to the Integrative Tumor Epidemiology Branch (ITEB) and contribute to the areas of metagenomics, spatial omics and somatic variant analysis in lung cancer research. The selected individual is expected to develop and apply computational tools to analyze complex microbial communities from environmental, clinical, or industrial samples, analysis of spatial transcriptomics and proteomics data to understand lung tissue microenvironment and cellular signatures, as well as detect and interpret somatic mutations in lung cancer. The bioinformatics analyst will work closely with DCEG investigators and CGR bioinformaticians and scientists with a high degree of independence. This role involves working with large-scale sequencing data, developing pipelines, and collaborating with interdisciplinary teams to derive biological insights, requiring the candidate to:

KEY ROLES/RESPONSIBILITIES

• Develop, implement, and optimize bioinformatics pipelines for metagenomic sequencing data analysis (e.g., taxonomic classification, functional annotation, and comparative genomics).
• Analyze high-throughput sequencing data from lung whole-genome sequencing (WGS), bulk RNA sequencing (RNA-seq), and 16S amplicon sequencing.
• Develop and maintain computational workflows for metagenomic analysis using tools such as Kraken2, Bracken, MetaPhlAn, and HUMAnN.
• Perform quality control and model batch effects in lung metagenomics data.
• Perform functional and taxonomic profiling of microbial communities to identify key patterns.
• Use statistical approaches to interpret lung metagenomics data and associate with clinical and multi-omics data.
• Develop robust pipeline for somatic variant analysis of WGS from lung cancer using tools like GATK, Mutect, Strelka.
• Perform copy number and structural variant analysis in lung cancer samples.
• Work with a multi-disciplinary team towards the development and analysis of reproducible, standardized workflows, in single-cell and spatial omics, by thoroughly researching the latest publications, developments and combining them with strong programming skills.
• Review, QC, and integrate single-cell and spatial datasets and perform downstream statistical analysis using phenotypic and clinical metadata.
• Maintain and document bioinformatics software and scripts for reproducibility and scalability.
• Present research findings in publications, reports, and scientific conferences.
• Lead instructional classes on bioinformatic approaches for somatic analysis of cancer.
• Develop interactive web-based instructional materials, using tools such as GitHub Pages.

BASIC QUALIFICATIONS

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

• Possession of a bachelor’s or master’s degree from an accredited college/university in genetics, genomics, bioinformatics, biostatistics, computer science, computational biology or another related field, 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 two (2) years of progressively responsible experience.
• The ability to construct practical computational pipelines for data parsing, quality control and analysis for large-scale genetic or genomics datasets.
• Strong programming skills (e.g., in R, Python) with experience in RStudio and Jupyter Notebooks.
• Demonstrable shell scripting skills (e.g., bash, awk, sed).
• Experience working in a Linux environment (especially a HPC environment or cloud).
• Ability to obtain and maintain a security clearance.

PREFERRED QUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

• Strong proficiency in programming (R and Bash) and GitHub.
• Previous experience with lung cancer genomics research.
• Strong experience analyzing high-throughput sequencing data including whole-genome sequencing data, bulk RNA sequencing, 16S rRNA sequencing.
• Strong experience with microbial ecology, genomics, and statistical analysis.
• Experience or familiarity with processing of single-cell and spatial omics data utilizing latest bioinformatics tools such as Cell Ranger, Space Ranger, Seurat, Scanpy, Squidpy, Cell2location etc.
• Experience working in Linux-based environments and using HPC (high-performance computing) clusters.
• Strong experience with large-scale multi-omics data integration (e.g., genomics, transcriptomics, metagenomics, meta-transcriptomics).
• Good 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.
• Understanding of software and workflow development best practices such as source control, test driven programming and continuous integration/deployment.
• 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

90,500.00 - 155,625.00

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