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The National Human Genome Research Institute (NHGRI), a major research component of the National Institutes of Health (NIH) and the Department of Health and Human Services (DHHS), is seeking exceptional candidates for a Staff Scientist position in the Intramural Research Program (IRP), Translational and Functional Genomics Branch (TFGB), Genomic Functional Analysis Section (GFAS).

About the position

GFAS investigates altered epigenetic patterns in cancer and genetic diseases to identify genomic loci that undergo aberrant regulation, including potential therapeutic targets and blood-based biomarkers. The GFAS and TFGB environments provide an exceptional platform for integrating experimental and computational genomics, supporting studies of human and microbial genomes as well as animal models of genetic disease. TFGB investigators drive innovation in functional genomics, systematic mutagenesis, developmental genomics, and computational analysis, advancing discoveries that inform clinical translation.

The Staff Scientist will lead efforts to develop and apply novel approaches to uncover biological mechanisms underlying disease. This includes conducting molecular, computational, and cell-based experiments with a focus on multi-omic data integration. The successful candidate will have demonstrated expertise in immunofluorescence microscopy, CRISPR/dCas9 systems, and liquid biopsy analysis, as well as proficiency in chromatin, DNA replication, and DNA repair studies. Competency in culturing cancer organoids is desirable. Experience elucidating causal mechanisms of splicing disruption in disease, performing digital ultra-sensitive PCR for liquid biopsy, and conducting genome-wide biomarker discovery using advanced sequencing technologies will be highly valued. Profiling and interpreting cancer responses to therapy will be a fundamental aspect of the research focus.

The ideal candidate will have broad vision, extensive skill sets and integrative abilities.

Required Technical Expertise

  • Molecular Biology: Conditional gene knockouts (including mESCs, PMEFs, and iPSCs); cell cycle and apoptosis analysis using FACS and Annexin V assays; Western blotting; immunofluorescence; light and fluorescent microscopy; PCR techniques (RT-PCR, PCR-RFLP, digital droplet, ultra-sensitive single molecule); molecular cloning; plasmid transformation and transfection; and short and long read library preparation.
  • Genomic and Epigenomic Technologies: Preparation, collection, and analysis of single cell ChIP-seq, ATAC-seq, and DNA methylation datasets. Experience with mass spectrometry sample preparation and dataset interpretation.
  • Analytical and Biochemical Skills: Proficiency in chemiluminescent metabolite estimation; experience with high throughput small molecule response testing.
  • Computational Approaches: Demonstrated capability in independent data analysis using high-performance computing clusters.

Responsibilities and Collaborative Roles

The Staff Scientist will provide technical and intellectual leadership within GFAS, supporting project design, data interpretation, and technology development for GFAS and collaborative NHGRI/NIH investigators. Responsibilities include writing and contributing to manuscripts and grant applications, assisting with resource and supply management, oversight of lab equipment and government resources, and mentoring junior researchers. Strong written and verbal communication skills are required, along with the ability to present complex research findings effectively to multidisciplinary teams.


What you'll need to apply

Applicants should send curriculum vitae, letter of interest and three names suitable for recommendation.

Contact name

Laura Elnitski

Contact email

elnitski@nih.gov

Qualifications

Candidates must have a Ph.D. or equivalent in Biochemistry, Genomics, or an equivalent field. Must have a minimum of seven years’ experience post-PhD in molecular and cell biology and genomics research. Ability for clinical and basic research with emphasis on gene editing, computing, and all aspects of tumor biology. Additionally, it is necessary for candidates to have a demonstrated background in data science, molecular and protein biology.

Disclaimer/Fine Print

U.S. citizens and permanent residents are eligible to apply.

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