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Bioinformatics Analyst III, ITEB, CGR
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BioSpace 2 days ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. Overview
The Frederick National Laboratory is operated by Leidos Biomedical Research, Inc. The lab addresses urgent problems in biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, nanotechnology in medicine, and responses to emerging infectious diseases. Program description and mission are described below. 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 collaborates with the NCI’s Division of Cancer Epidemiology and Genetics (DCEG). Our team leverages cutting-edge technologies to investigate genetic, epigenetic, transcriptomic, proteomic, and molecular factors that drive cancer susceptibility and outcomes, with a mission to discover the causes of cancer and advance prevention strategies through DCEG’s research. Our bioinformatics team supports DCEG’s multidisciplinary studies by providing 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 platforms. We analyze germline and somatic variants, structural variations, copy number variations, gene and isoform expression, base modifications, viral and bacterial genomics, and more. We work with large population databases to inform and validate GWAS signals and study associations between genetic variation and gene expression, proteins, metabolites, and polygenic risk scores across populations. We develop and implement cloud-enabled pipelines and data analysis methodologies, blending traditional bioinformatics with machine learning, deep learning, and generative AI. We emphasize reproducibility through containerization, workflow management, benchmarking, and thorough workflow documentation. Our infrastructure supports a high-performance computing (HPC) cluster, cloud environments, and curation of large datasets. The successful candidate will provide analytical support to the Integrative Tumor Epidemiology Branch (ITEB) and contribute to cancer research areas such as GWAS, germline and somatic variant analysis, single-cell RNA sequencing, and proteomics expression analysis. They will install, troubleshoot, and execute analytical pipelines on Unix/Linux and cloud platforms, and will use public bioinformatics and genomic databases and 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). Ability to run and interpret variant calling results, including SNP/indel, microsatellite, and structural variants using current community standards. Conduct association analyses of large GWAS datasets using software such as PLINK and Genome-wide Complex Trait Analysis (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, standardized workflows for single-cell and proteomics studies by integrating latest research developments with strong programming skills. Review, QC, and integrate single-cell and proteomic datasets, performing downstream statistical analysis using phenotypic and clinical metadata. Demonstrate strong teamwork and communication skills, with the ability to effectively 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 resulting from research projects. Basic Qualifications
Possession of a bachelor’s degree from an accredited college or university in bioinformatics, computer science, computational biology, or related field. Foreign degrees must be 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 data parsing, quality control and analysis for large-scale genetic or genomics datasets. Strong programming skills in at least two of R, Python, C++, with experience in RStudio and Jupyter Notebooks. Strong experience analyzing high-throughput sequencing data including whole-genome, bulk and single-cell RNA sequencing. Experience in standard genetic association analysis software like PLINK, SAIGE, regenie, GCTA etc. Demonstrable shell scripting skills (e.g., bash, awk, sed). Experience working in a Linux environment (especially an HPC environment or cloud). Ability to obtain and maintain a security clearance. Preferred Qualifications
Strong proficiency in programming (R, Python and Bash) and GitHub. Provide support for analysis of genomic data from epidemiological studies, including data manipulation and integrated genomic analyses. Prepare reports and presentations detailing analyses. Proficiency with core statistical and bioinformatics methods (linear regression, logistic regression, eQTL analysis, LDscore regression, fine-mapping, credible set and colocalization analysis). Experience processing single-cell data with tools such as Cell Ranger, Seurat, Scanpy, Squidpy, Cell2location, etc. Familiarity with cancer genomics data sources (dbGaP, TCGA, ENCODE, 1000 Genomes, GTEX, gnomAD, cBioPortal, TCPA). Experience working in Linux environments and HPC clusters. Strong experience with large-scale multi-omics data integration. Knowledge of containerization (Docker/Singularity), JIRA and GitHub for project management. Understanding of software and workflow development best practices (source control, test-driven development, CI/CD). Strong analytical and problem-solving skills with attention to detail. Strong communication skills and ability to work independently and 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, 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 qualified applicants with criminal histories consistent with relevant laws. Pay and Benefits
Pay and benefits are fundamental to any career decision. The posted pay range is 109,600.00 - 188,250.00 and is a general guideline, not a guarantee of compensation. Employment benefits include competitive compensation, health and wellness programs, income protection, paid leave and retirement. The salary varies based on hours for part-time roles and other factors such as responsibilities, education, experience, knowledge, skills, and abilities as well as internal equity and market data. 109,600.00 - 188,250.00 Note: The posted salary range is a general guideline and may vary. Seniority level Mid-Senior level Employment type Full-time Job function Research, Analyst, and Information Technology Industries Internet News Referrals increase your chances of interviewing at BioSpace by 2x Get notified about new Bioinformatics Analyst jobs in Rockville, MD.
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Bioinformatics Analyst III, ITEB, CGR
role at
BioSpace 2 days ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. Overview
The Frederick National Laboratory is operated by Leidos Biomedical Research, Inc. The lab addresses urgent problems in biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, nanotechnology in medicine, and responses to emerging infectious diseases. Program description and mission are described below. 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 collaborates with the NCI’s Division of Cancer Epidemiology and Genetics (DCEG). Our team leverages cutting-edge technologies to investigate genetic, epigenetic, transcriptomic, proteomic, and molecular factors that drive cancer susceptibility and outcomes, with a mission to discover the causes of cancer and advance prevention strategies through DCEG’s research. Our bioinformatics team supports DCEG’s multidisciplinary studies by providing 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 platforms. We analyze germline and somatic variants, structural variations, copy number variations, gene and isoform expression, base modifications, viral and bacterial genomics, and more. We work with large population databases to inform and validate GWAS signals and study associations between genetic variation and gene expression, proteins, metabolites, and polygenic risk scores across populations. We develop and implement cloud-enabled pipelines and data analysis methodologies, blending traditional bioinformatics with machine learning, deep learning, and generative AI. We emphasize reproducibility through containerization, workflow management, benchmarking, and thorough workflow documentation. Our infrastructure supports a high-performance computing (HPC) cluster, cloud environments, and curation of large datasets. The successful candidate will provide analytical support to the Integrative Tumor Epidemiology Branch (ITEB) and contribute to cancer research areas such as GWAS, germline and somatic variant analysis, single-cell RNA sequencing, and proteomics expression analysis. They will install, troubleshoot, and execute analytical pipelines on Unix/Linux and cloud platforms, and will use public bioinformatics and genomic databases and 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). Ability to run and interpret variant calling results, including SNP/indel, microsatellite, and structural variants using current community standards. Conduct association analyses of large GWAS datasets using software such as PLINK and Genome-wide Complex Trait Analysis (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, standardized workflows for single-cell and proteomics studies by integrating latest research developments with strong programming skills. Review, QC, and integrate single-cell and proteomic datasets, performing downstream statistical analysis using phenotypic and clinical metadata. Demonstrate strong teamwork and communication skills, with the ability to effectively 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 resulting from research projects. Basic Qualifications
Possession of a bachelor’s degree from an accredited college or university in bioinformatics, computer science, computational biology, or related field. Foreign degrees must be 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 data parsing, quality control and analysis for large-scale genetic or genomics datasets. Strong programming skills in at least two of R, Python, C++, with experience in RStudio and Jupyter Notebooks. Strong experience analyzing high-throughput sequencing data including whole-genome, bulk and single-cell RNA sequencing. Experience in standard genetic association analysis software like PLINK, SAIGE, regenie, GCTA etc. Demonstrable shell scripting skills (e.g., bash, awk, sed). Experience working in a Linux environment (especially an HPC environment or cloud). Ability to obtain and maintain a security clearance. Preferred Qualifications
Strong proficiency in programming (R, Python and Bash) and GitHub. Provide support for analysis of genomic data from epidemiological studies, including data manipulation and integrated genomic analyses. Prepare reports and presentations detailing analyses. Proficiency with core statistical and bioinformatics methods (linear regression, logistic regression, eQTL analysis, LDscore regression, fine-mapping, credible set and colocalization analysis). Experience processing single-cell data with tools such as Cell Ranger, Seurat, Scanpy, Squidpy, Cell2location, etc. Familiarity with cancer genomics data sources (dbGaP, TCGA, ENCODE, 1000 Genomes, GTEX, gnomAD, cBioPortal, TCPA). Experience working in Linux environments and HPC clusters. Strong experience with large-scale multi-omics data integration. Knowledge of containerization (Docker/Singularity), JIRA and GitHub for project management. Understanding of software and workflow development best practices (source control, test-driven development, CI/CD). Strong analytical and problem-solving skills with attention to detail. Strong communication skills and ability to work independently and 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, 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 qualified applicants with criminal histories consistent with relevant laws. Pay and Benefits
Pay and benefits are fundamental to any career decision. The posted pay range is 109,600.00 - 188,250.00 and is a general guideline, not a guarantee of compensation. Employment benefits include competitive compensation, health and wellness programs, income protection, paid leave and retirement. The salary varies based on hours for part-time roles and other factors such as responsibilities, education, experience, knowledge, skills, and abilities as well as internal equity and market data. 109,600.00 - 188,250.00 Note: The posted salary range is a general guideline and may vary. Seniority level Mid-Senior level Employment type Full-time Job function Research, Analyst, and Information Technology Industries Internet News Referrals increase your chances of interviewing at BioSpace by 2x Get notified about new Bioinformatics Analyst jobs in Rockville, MD.
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