Computational Biologist

The Cancer Genomics Research Laboratory (CGR) investigates the contribution of germline and somatic genetic variation to cancer susceptibility and outcomes in support of the National Cancer Institute (NCI)'s Division of Cancer Epidemiology and Genetics (DCEG). Working in concert with epidemiologists, biostatisticians and basic research scientists in DCEG's intramural research program, CGR provides the capacity to conduct genome-wide discovery studies and targeted regional approaches to identify the heritable and acquired determinants of various forms of cancer. This includes the design and analysis of high throughput studies using various types of “-omics” technologies such as sequence- and array- based genome-wide association studies, and generation of comprehensive data on histological and molecular profiling of tumors and their precursors to identify environmental and germline risk factors for cancer through integrative analytics. We are seeking a highly motivated Computational Biologist to join the bioinformatics team at the CGR and provide senior analytical support to DCEG, primarily focused on comprehensive molecular profiling studies of various types of cancer. Working with DCEG investigators, external collaborators, CGR management and staff, the successful incumbent will provide independent and strong support to the extensive DCEG research portfolio, specifically:

KEY ROLES/RESPONSIBILITIES

• Performing a wide range of bioinformatics analyses for tumor/normal sequencing data including germline and somatic SNV/indel calling, Structure Variant (SV) detection, Copy Number Variation (CNV) detection, and other RNA and DNA sequencing related analyses.
• Help guide the development of new bioinformatics pipelines through adequate benchmarking and QC.
• Working on the Cloud/HPC environment to effectively process large scale datasets.
• Performing curation, QC, harmonization and evaluation of large-scale data sets from a variety of technical platforms, including bulk DNA, RNA, methylation sequencing from Illumina and Pacific Biosciences
• Performing downstream analyses including variant filtering/validation, burden test, statistical analysis, and integrative analysis.
• Organizing results into clear presentations and concise summaries of work, in formats useful for scientific interpretation
• Incumbent will be expected to work closely with DCEG PIs in support of scientific manuscript development, submission, revision activities with significant coauthor and potentially lead authorship opportunities

BASIC QUALIFICATIONS

• Possession of a Doctoral degree from an accredited college/university according to the Council for Higher Education Accreditation (CHEA) in Bioinformatics, Computational Biology or related field (Additional qualifying experience may be substituted for the required education). Foreign degrees must be evaluated for U.S equivalency.
• In addition to educational requirements, a minimum of two (2) years of work experience with sequencing analysis/bioinformatics programming.
• Demonstrated experience in integrative molecular analysis for tumor profiling
• Extensive work experience with human sequencing data, tumor/normal analysis using a wide range of contemporary, open-source/commercial bioinformatics tools such as GATK, Muse, SomaticSeq, Manta, Meerkat, FACETS, ASCAT, Plink, etc.
• Adept at review of current scientific literature for advances in analytical approaches and identification of new tools
• Experience with publicly available data sources (such as dbGaP, TCGA, GDC, ENCODE, 1000 Genomes, gnomAD, TARGET, GTEX) and diverse genomic annotations
• Proficiency in Shell, Python, R, Java, and/or C.
• Work experience with High-performance computing and large-scale data processing
• Work experience with software development on Linux system
• Experience with molecular and population genetics
• Must be able to obtain and maintain a security clearance

PREFERRED QUALIFICATIONS

• Experience with AWS EC2/ELB/S3 or other cloud computing environments
• Experience with Snakemake or other workflow languages
• Experience with Singularity or other container-based platforms
• Experience with statistics and algorithm development
• Careful attention to detail. Must be analytical, flexible, innovative, and self-motivated
• Ability to organize and execute multiple projects in parallel
• Ability to carry out a wide range of bioinformatics techniques and analyses, and benchmark/troubleshoot with minimal supervision
• Ability to quickly learn and implement new bioinformatics tools and techniques
• Excellent written and oral communication-ability to communicate clearly and effectively with staff and other groups within CGR and DCEG, and able to interpret data and write scientific reports as well as other written communications

Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)