Medical Science & Computing is searching for a Clinical Computational Genomics Specialist to join our Bioinformatics team at NIH. This opportunity is a permanent, full-time position with MSC and it is on-site at the NIH in Rockville and Bethesda, MD.
The candidate will operate in a large (50+) multi-disciplinary group providing bioinformatics and computational biology support, training, and consultation services to NIH researchers. The successful candidate for this position will be self-directed, highly collaborative and will provide leadership as a genomics expert. The successful candidate must have excellent written and verbal communication skills to interact with the research community and find the right solution for their diverse scientific computing needs.
The successful candidate will work cooperatively with current computational biology specialists to:
Implement, design, develop, and innovate current and emerging computational biology and bioinformatics algorithms to analyze, manage, interpret, visualize, and illustrate original scientific data
Enter into scientific collaborations with physicians and scientists that include the potential for authorships and acknowledgements in publications
Gather detailed requirements from stakeholders and identify existing tools to perform the novel analyses or develop algorithms/tools to perform the analysis
Document and manage collaborative and consultant assistance and training provided to researchers
Provide on-site, on-demand support and troubleshooting to researchers in the use of computational biology software
Research, design, and deliver training materials to effectively communicate, promote, and advance computational biology techniques and software usage by NIH researchers
Remain abreast on current and emerging computational biology technologies and tools
Partner with software developers to integrate genomic software solutions within enterprise platforms
Ph.D. (or MS with 3+ years of relevant experience) in computational biology, bioinformatics, genetics or related life, physical, or computational sciences with at least one publication demonstrating the use or development of computational biology applications.
Good understanding of genomics, molecular biology, and technologies such as qPCR and next-generation sequencing.
Two years of experience in the analysis of large-scale genomic sequencing data including variant analysis from whole genome or exome sequencing data and experience with a broad spectrum of relevant open-source software or pipelines (e.g., BWA, GATK, SnpEff, VEP, etc.)
Proficiency in the use of UNIX/Linux and its command-line environment, including scripting (e.g., Python, R, Perl, shell, or Ruby).
Experience with a high-performance parallel computing environment
Strong interpersonal, presentation, written, and oral communication skills to convey computational biology principles and concepts to non-specialists in a clear and precise manner and advise on relevant software and tools with a dedication to customer satisfaction.
Ability to work independently or as part of a multi-disciplinary team
Excellent troubleshooting and problem-solving skills, including the ability to learn new software quickly.
Ability to concurrently work on multiple complex projects with effective time management skills, a high level of personal and professional drive and initiative, and attention to detail
Additional Desired Skills and Experience
Experience with genomic diagnosis of rare diseases and filtering variants using family-based genetic models (e.g., autosomal recessive/dominant, compound heterozygous, etc.), including experience with relevant related tools for finding disease-causing variants (e.g. VAAST/pVAAST, GEMINI)
Experience with structural variation analysis from next-generation sequencing data
Experience constructing pipelines in open architecture platforms (especially WDL/Cromwell, but also Snakemake, others), including end-to-end tasks for NGS analysis tools
Experience with genetic association methods (case-control, burden testing, family-based linkage analysis)
Experience with RNA-seq + genome assembly using tools such as HISAT2, STAR, DESeq2
Familiarity with common methods of statistical analysis using R, SAS, or related software.
Familiarity with algorithms and algorithm development for bioinformatics, including composing, editing, and compiling open-source code.
Familiarity with problems and bottlenecks associated with storage and management of genomic-scale data.
Familiarity with the use of open-source bioinformatics applications employing ontologies, pathways, and/or networks, at both the individual gene and genomic scales.
Strong background in molecular/cellular biology, immunology, and/or virology, including “bench” experience.
Ability to propose and develop new methodologies for analyzing biomedical data
Medical Science & Computing is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected Veteran status.
About Medical Science and Computing
Medical Science & Computing (MSC) is an exciting growth oriented company, dedicated to providing mission critical scientific and technical services to the Federal Government. We have a distinguished history of supporting the National Institutes of Health (NIH) and other government agencies. MSC offers a dynamic and upbeat work environment, excellent benefits and career growth opportunities.