Bioinformatics Analyst I, Biostatistics Branch, CGR – Hybrid Remote/Onsite in Rockville, MD in Frederick National Laboratory

Job title: Bioinformatics Analyst I, Biostatistics Branch, CGR - Hybrid Remote/Onsite Company: Frederick National Laboratory Job description: Bioinformatics Analyst I, Biostatistics Branch, CGR - Hybrid Remote/Onsite Job ID: req3372 Employee Type: exempt full-time Division: Clinical Research Program Facility: Rockville: 9609 MedCtrDr Location: 9609 Medical Center Dr, Rockville, MD 20850 USA The Frederick National Laboratory is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI) and 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 The Cancer Genomics Research (CGR) laboratory in Gaithersburg, MD, is an advanced, fast-paced, high-throughput organization dedicated to the support of molecular, genetic and epidemiologic studies for investigators at the National Cancer Institute's Division of Cancer Epidemiology & Genetics (DCEG). The Division includes over 70 principal investigators (PIs) who are at the forefront in cancer epidemiology, genetics, and biostatistics and conduct sophisticated multidisciplinary family- and population-based research utilizing cutting-edge multi-omics technologies to discover the genetic and environmental determinants of cancer. The investigators at DCEG are uniquely positioned to design exemplary studies by collaborating with investigators globally and lead the design and analysis of large-scale genome-wide association studies, studies of tumor characteristics using integrated genomic data analysis and molecular epidemiologic studies based on novel metabolomic and macrobiotic assays. Within DCEG, the Biostatistics Branch (BB) staff and Investigators develop statistical methods and data resources to strengthen observational studies, intervention trials, and laboratory investigations of cancer. DCEG/BB is adding computational support, to be provided through CGR, to support methods for large genomic studies including GWAS analysis, somatic mutation analysis, and integrative tumor analysis. We are seeking a highly motivated bioinformatics analyst to join the bioinformatics team at the CGR and provide dedicated analytical support for BB investigators while working in concert with DCEG investigators, external collaborators, CGR management and staff. The successful incumbent will provide support to the BB analytical efforts, and will have the opportunity to: KEY ROLES/RESPONSIBILITIES • Work closely and learn from expert principal investigators (PIs) within the Biostatistics Branch while supporting a broad portfolio of DCEG projects • Utilize strong programming expertise to learn, test, benchmark and apply new software packages in a high-performance computing cluster (HPC) and/or cloud environment. • Review, QC, and integrate data from multiple sources (multi-omics studies), primarily focused on germline genotyping and sequencing data, with some additional somatic mutations, copy number alterations, transcription, and methylation data for cancers. • Organize results into clear presentations and concise summaries of work, in formats useful for scientific interpretation • Document all analyses and pipelines clearly using collaborative tools and share with teams in support of reproducible and FAIR research • Work closely with DCEG and BB PIs and senior bioinformaticians 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 degree from an accredited college or university according to the Council for Higher Education Accreditation (CHEA) in bioinformatics, computer science, computational biology, biostatistics or related field. Additional qualifying experience may be substituted for the required education • 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: • Strong programming skills in Python, R and Bash scripting with experience working on HPC • Candidates with bioinformatics/computer/biostatistics science background or strong

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