Bioinformatics Analyst I - Frederick National Laboratory for Cancer Research : Job Details

Bioinformatics Analyst I

Job ID: req4253Employee Type: exempt full-timeDivision: Clinical Research ProgramFacility: Rockville: 9615 MedCtrDrLocation: 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 an enthusiastic 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.

We are looking for a highly motivated bioinformatics analyst to provide dedicated analytical support for the Laboratory of Translational Genomics (LTG), working in concert with DCEG investigators, external collaborators, CGR management and staff. The successful incumbent will provide support to the LTG analytical efforts, and will have the opportunity to:

KEY ROLES/RESPONSIBILITIES

• Work closely and learn from expert principal investigators within LTG while supporting a broad portfolio of projects.
• Review, QC, and integrate data from multiple sources (multi-omics studies).
• Develop and document the pipelines designed for High Performance clusters and to be scalable.
• Maintain and analyze genomic datasets related to Hi-Chip, sc-RNA-seq, long-read sequencing, etc.
• Sequence Read Archive (SRA) database retrieval and deposition, mining of public databases, such as TCGA, GTEx and other resources.
• Assist with data analysis, organize results into clear presentations and concise summaries of work, in formats useful for scientific interpretation.
• Document all analyses and pipelines used in support of reproducible and FAIR research.
• Work closely with LTG PIs in support of scientific manuscript development, submission, revision activities with significant co-authorship opportunities.

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.
• 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).
• 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:

• Experience with processing and analyzing large datasets for at least one of the following: GWAS, whole genome/exome sequencing, transcriptomics or other popular next-generation sequencing applications.
• Proficiency with core statistical and bioinformatics methods (linear regression, logistic regression, eQTL analysis, LDscore regression, credible set and colocalization analysis, etc.).
• Familiarity with public genomic tools, databases, and utilities (UCSC Genome Browser, TCGA, ENCODE, 1000 Genomes, dbGAP, GTEX, SRA NCBI, etc.).
• Experience with various environment/dependency management tools (e.g. pip, venv, conda, renv).
• Knowledge of DevOps tools and technologies, such as Docker/Singularity, GitHub for code management.
• Team-oriented with demonstrated ability to self-educate in current bioinformatics techniques and resources.
• Ability to multi-task in a fast-paced environment, organize and execute multiple projects in parallel both independently and as part of working groups.

Commitment to Non-DiscriminationAll 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

74,800.00 - 128,625.00

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