BioSpace
Job ID: req4285
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 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 GWAS, methylation, targeted, whole-exome, whole-transcriptome and whole-genome sequencing, as well as viral and metagenomic studies from 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. We also integrate technologies such as single cell, multiomics, spatial transcriptomics, and proteomics, in collaboration with CGR’s Functional and Molecular and Digital Pathology Laboratory groups. We regularly analyze large population databases such as All of Us, UK Biobank, gnomAD and 1000 Genomes to inform and validate GWAS signals and study links between genetic variation and gene expression, proteins, metabolites and polygenic risk scores across populations.
Our bioinformatics team develops cloud-enabled pipelines and data analysis methodologies, blending traditional bioinformatics and statistics with machine learning, deep learning, and generative AI models. We emphasize reproducibility through containerization, workflow management, benchmarking, and documentation. Our infrastructure and data management team maintains a high-performance computing (HPC) cluster, provisions cloud environments, and curates large datasets.
The successful candidate will provide analytical support to the Integrative Tumor Epidemiology Branch (ITEB) and contribute to cancer research in areas such as GWAS, germline and somatic variant analysis, single-cell RNA sequencing, and proteomics expression analysis. The analyst will support installation, troubleshooting, and execution of analytical pipelines on Unix/Linux and cloud platforms, and will leverage publicly available bioinformatics and genomic databases and analysis pipelines to process data types including genome-wide genotyping arrays, long-read sequencing, gene expression, proteomics, and methylation profiling across diverse tissues and cancer types.
Key Roles/Responsibilities
Develop, implement, and optimize analytical pipelines for germline and somatic variant analysis from short- and long-read whole-genome sequencing (WGS). Run and interpret variant calling results (SNP/indel, microsatellite, structural variants) using current community standards.
Conduct association analyses of large GWAS datasets using software such as PLINK and GCTA.
Apply statistical approaches to interpret diverse genetic and genomic datasets and integrate findings with clinical and multi-omics data.
Collaborate with a multidisciplinary team to develop and analyze reproducible workflows for single-cell and proteomics studies, integrating latest research with strong programming skills.
Review, QC, and integrate single-cell and proteomic datasets; perform downstream statistical analysis using phenotypic and clinical metadata.
Demonstrate teamwork and communication skills; learn and apply new bioinformatics techniques and resources.
Maintain and document bioinformatics software and scripts to ensure reproducibility and scalability.
Participate in group meetings, present findings, and contribute to publications from research projects.
Basic Qualifications
Bachelor’s degree from an accredited institution in bioinformatics, computer science, computational biology or related field (foreign degrees evaluated for U.S. equivalency).
Minimum of six (6) years of related analytical or bioinformatics pipeline development experience.
Ability to construct practical computational pipelines for processing large-scale genetic/genomics data.
Strong programming skills in at least two of R, Python, C++, with experience in RStudio and Jupyter Notebooks.
Experience analyzing high-throughput sequencing data including WGS, bulk and single-cell RNA sequencing.
Experience with standard genetic association software (PLINK, SAIGE, regenie, GCTA, etc.).
Shell scripting skills (e.g., bash, awk, sed).
Experience in Linux environments (HPC or cloud).
Ability to obtain and maintain a security clearance.
Preferred Qualifications
Strong programming proficiency (R, Python, Bash) and GitHub.
Experience analyzing genomic data from epidemiological studies, including reporting and presenting analyses.
Familiarity with core statistical and bioinformatics methods (e.g., linear/logistic regression, eQTL, LD score regression, fine-mapping, colocalization).
Experience processing single-cell data with tools like Cell Ranger, Seurat, Scanpy, Squidpy, Cell2location.
Knowledge of cancer genomics resources (dbGaP, TCGA, ENCODE, gnomAD, cBioPortal, TCPA).
Experience with HPC environments and Linux, and large-scale multi-omics data integration.
Experience with environment/dependency management and workflow systems (Snakemake, Nextflow).
Knowledge of containerization (Docker/Singularity) and project management tools (JIRA, GitHub).
Understanding of software/workflow development best practices (version control, tests, CI/CD).
Strong analytical, problem-solving, and communication skills; ability to work both independently and in 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, disability, genetic information, pregnancy, family status, marital status, veteran or military status, or any other basis prohibited by law. Leidos will also consider qualified applicants with criminal histories where permitted by law.
Pay And Benefits Pay and benefits are fundamental to any career decision. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. The posted salary range is 109,600.00 - 188,250.00 full-time equivalent; actual offers depend on responsibilities, education, experience, and market data. Part-time hours may adjust the salary.
Seniority level : Mid-Senior level
Employment type : Full-time
Job function : Research, Analyst, and Information Technology
Industries : Internet News
The description above reflects the role and qualifications; future postings may reference additional details.
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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 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 GWAS, methylation, targeted, whole-exome, whole-transcriptome and whole-genome sequencing, as well as viral and metagenomic studies from 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. We also integrate technologies such as single cell, multiomics, spatial transcriptomics, and proteomics, in collaboration with CGR’s Functional and Molecular and Digital Pathology Laboratory groups. We regularly analyze large population databases such as All of Us, UK Biobank, gnomAD and 1000 Genomes to inform and validate GWAS signals and study links between genetic variation and gene expression, proteins, metabolites and polygenic risk scores across populations.
Our bioinformatics team develops cloud-enabled pipelines and data analysis methodologies, blending traditional bioinformatics and statistics with machine learning, deep learning, and generative AI models. We emphasize reproducibility through containerization, workflow management, benchmarking, and documentation. Our infrastructure and data management team maintains a high-performance computing (HPC) cluster, provisions cloud environments, and curates large datasets.
The successful candidate will provide analytical support to the Integrative Tumor Epidemiology Branch (ITEB) and contribute to cancer research in areas such as GWAS, germline and somatic variant analysis, single-cell RNA sequencing, and proteomics expression analysis. The analyst will support installation, troubleshooting, and execution of analytical pipelines on Unix/Linux and cloud platforms, and will leverage publicly available bioinformatics and genomic databases and analysis pipelines to process data types including genome-wide genotyping arrays, long-read sequencing, gene expression, proteomics, and methylation profiling across diverse tissues and cancer types.
Key Roles/Responsibilities
Develop, implement, and optimize analytical pipelines for germline and somatic variant analysis from short- and long-read whole-genome sequencing (WGS). Run and interpret variant calling results (SNP/indel, microsatellite, structural variants) using current community standards.
Conduct association analyses of large GWAS datasets using software such as PLINK and GCTA.
Apply statistical approaches to interpret diverse genetic and genomic datasets and integrate findings with clinical and multi-omics data.
Collaborate with a multidisciplinary team to develop and analyze reproducible workflows for single-cell and proteomics studies, integrating latest research with strong programming skills.
Review, QC, and integrate single-cell and proteomic datasets; perform downstream statistical analysis using phenotypic and clinical metadata.
Demonstrate teamwork and communication skills; learn and apply new bioinformatics techniques and resources.
Maintain and document bioinformatics software and scripts to ensure reproducibility and scalability.
Participate in group meetings, present findings, and contribute to publications from research projects.
Basic Qualifications
Bachelor’s degree from an accredited institution in bioinformatics, computer science, computational biology or related field (foreign degrees evaluated for U.S. equivalency).
Minimum of six (6) years of related analytical or bioinformatics pipeline development experience.
Ability to construct practical computational pipelines for processing large-scale genetic/genomics data.
Strong programming skills in at least two of R, Python, C++, with experience in RStudio and Jupyter Notebooks.
Experience analyzing high-throughput sequencing data including WGS, bulk and single-cell RNA sequencing.
Experience with standard genetic association software (PLINK, SAIGE, regenie, GCTA, etc.).
Shell scripting skills (e.g., bash, awk, sed).
Experience in Linux environments (HPC or cloud).
Ability to obtain and maintain a security clearance.
Preferred Qualifications
Strong programming proficiency (R, Python, Bash) and GitHub.
Experience analyzing genomic data from epidemiological studies, including reporting and presenting analyses.
Familiarity with core statistical and bioinformatics methods (e.g., linear/logistic regression, eQTL, LD score regression, fine-mapping, colocalization).
Experience processing single-cell data with tools like Cell Ranger, Seurat, Scanpy, Squidpy, Cell2location.
Knowledge of cancer genomics resources (dbGaP, TCGA, ENCODE, gnomAD, cBioPortal, TCPA).
Experience with HPC environments and Linux, and large-scale multi-omics data integration.
Experience with environment/dependency management and workflow systems (Snakemake, Nextflow).
Knowledge of containerization (Docker/Singularity) and project management tools (JIRA, GitHub).
Understanding of software/workflow development best practices (version control, tests, CI/CD).
Strong analytical, problem-solving, and communication skills; ability to work both independently and in 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, disability, genetic information, pregnancy, family status, marital status, veteran or military status, or any other basis prohibited by law. Leidos will also consider qualified applicants with criminal histories where permitted by law.
Pay And Benefits Pay and benefits are fundamental to any career decision. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. The posted salary range is 109,600.00 - 188,250.00 full-time equivalent; actual offers depend on responsibilities, education, experience, and market data. Part-time hours may adjust the salary.
Seniority level : Mid-Senior level
Employment type : Full-time
Job function : Research, Analyst, and Information Technology
Industries : Internet News
The description above reflects the role and qualifications; future postings may reference additional details.
#J-18808-Ljbffr