Staff Scientist

The mission of the NINDS Bioinformatics Core is to provide omics-based analysis & bioinformatics-related application development support for the NINDS institute. The Core fulfills hundreds of analysis requests each year and develops and maintains several custom applications. To meet these needs, the Core is staffed by Scientific Analysts and Scientific Application Developers, who work together in an integrated fashion.

Our omics-based analysis requests include, but are not limited to, next-generation sequencing analysis (e.g., WGS, WXS, RNA-Seq, scRNA-Seq, ChIP-Seq, PhIP-Seq, and Pathogen-Seq), microarray analysis, serology analysis, mass spectrometry analysis, metabolomic analysis, promoter analysis, Q-RT-PCR analysis, traditional sequence analysis, phylogenetic analysis, RNA structure and function prediction, miRNA target prediction, comparative genomics, and protein structure analysis. The goal of these requests may include class-discovery, biomarker discovery, predictive modeling, network discovery, mechanism deconvolution, target discovery, and pathogen discovery. Our core also performs development-related requests including custom scripting, database design and development, full-stack application development encompassing backend, middleware, and frontend components, API and systems integration, workflow and pipeline development, testing and performance optimization, and the deployment and maintenance of these applications in their final production environments.

Prospective Staff Scientists will work as a Scientific Analyst in our Core, report directly to the Core's Director, and be responsible for providing omics-based analysis support to NINDS investigators and staff as needed. They will be expected to conduct analyses independently and in a time-efficient manner using robust, defensible methods. Assisting in the interpretation of results and the generation of novel hypotheses or conclusions is also to be anticipated. Staff scientists may be asked to present their analysis results in a clear and concise manner to audiences who may not be familiar with bioinformatics practices. Our staff is also expected to providing training on the use of bioinformatics tools and databases that are licensed by NIH and/or publicly available.

Interested applicants should have a PhD in bioinformatics, computational biology, and/or a closely related field with at least four (4) years of relevant experience. The ideal candidate will have strong expertise in analyzing high-throughput data from complex experimental designs, including but not limited to data cleaning, data normalization, outlier assessment, data analysis, modeling, results interpretation, and visualization.

Experience analyzing specific high-throughput data types, including, but not limited to, WGS, WXS, RNA-Seq, scRNA-Seq, ChIP-Seq, PhIP-Seq, Pathogen-Seq, targeted resequencing, and microarray data (one-color and two-color), is also required.

Candidates should have experience submitting high-throughput datasets to public repositories and an excellent understanding of applied statistics. Excellent proficiency in R or Python is required, as is proven experience working in a high-performance computing environment and using open-source command-line tools for high-throughput data analysis.

Candidates must demonstrate a proven ability to interact and work well with others, multitask effectively, and meet or exceed expectations for agreed-upon analysis deliverables. In addition, candidates should also have a strong publication record demonstrating their relevant experience and technical expertise. Applicants with experience mentoring trainees and managing collaborative research projects will be prioritized. Excellent written and oral communication skills are essential.

The position is subject to a background check. U.S. citizens and permanent residents are eligible to apply. NIH welcomes foreign nationals with the exception of individuals from this list.