Genomic Specialist, Transcriptomics

Rockville, Maryland
Jan 17, 2022
Science/R&D, Genomics
Required Education
Position Type
Full time

We are currently searching for a Genomics Specialist, Transcriptomics to provide support to the National Institutes of Health (NIH). This opportunity is a full-time position with MSC, and it is on-site in Rockville, MD.


Duties & Responsibilities
  • 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 other graduate degree with equivalent 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.
  • Demonstrated proficiency in the analysis of large-scale transcriptomics data (especially RNA-seq, scRNA-seq, and RNA velocity) and experience with a broad spectrum of relevant open-source software (Cellranger, seurat, scanpy, velocyto, etc.) or pipelines (DESeq2, Salmon, Kallisto, etc.).
  • Experience working with relevant genomic databases and browsers and their annotations (NCBI, Refseq, Ensembl, GEO, IGV, UCSC Genome Browser.
  • Proficiency in the use of UNIX/Linux and its command-line environment, including scripting (shell, Perl, Python, etc.).
  • Experience with a high-performance parallel computing environment (e.g., SGE, PBS).
  • Familiarity with common methods of statistical analysis using R, python or related software.
  • 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.
  • Proficiency with the use of open-source bioinformatics applications employing ontologies, pathways, and/or networks, at both the individual gene and genomic scales


Preferred qualifications:

  • Familiarity with denovo genome assembly and annotation and tools (e.g. Canu, SPAdes, RAST).
  • Experience constructing pipelines in open architecture platforms (WDL/Cromwell, but also Snakemake, others), including end-to-end tasks for NGS analysis tools.
  • Familiarity with problems and bottlenecks associated with storage and management of genomic-scale data.
  • Strong background in molecular/cellular biology, immunology, and/or virology, including “bench” experience.
  • Proficiency in the analysis of a variety large-scale genomic sequencing data including ChIP-Seq, ATAC-Seq, and Methyl-Seq for example.
  • Familiarity with analysis of variant analysis from whole genome or whole exome sequencing data and experience with a broad spectrum of relevant open-source software or pipelines (BWA, HiSAT, STAR, GATK, SnpEff, VEP, DESeq, etc.).






Due to our contractual requirements, to be eligible for this role, you must be fully vaccinated against COVID-19 at time of hire.  

Company Description

Dovel Technologies and its Family of Companies (Medical Science & Computing and Ace Info Solutions) was acquired in October 2021.


Guidehouse is a leading global provider of consulting services to the public sector and commercial markets, with broad capabilities in management, technology, and risk consulting. By combining our public and private sector expertise, we help clients address their most complex challenges and navigate significant regulatory pressures focusing on transformational change, business resiliency, and technology-driven innovation. Across a range of advisory, consulting, outsourcing, and digital services, we create scalable, innovative solutions that help our clients outwit complexity and position them for future growth and success. The company has more than 12,000 professionals in over 50 locations globally. Guidehouse is a Veritas Capital portfolio company, led by seasoned professionals with proven and diverse expertise in traditional and emerging technologies, markets, and agenda-setting issues driving national and global economies.


Guidehouse is an Equal Employment Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, citizenship status, military status, protected veteran status, religion, creed, physical or mental disability, medical condition, marital status, sex, sexual orientation, gender, gender identity or expression, age, genetic information, or any other basis protected by law, ordinance, or regulation.


Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance, including the Fair Chance Ordinance of Los Angeles and San Francisco.


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