Staff Scientist 1 (Interdisciplinary Bioinformatics Project Team Leader)

National Library of Medicine, U.S. National Institutes of Health
Intramural Research Program
United States Maryland Bethesda


The Interdisciplinary Bioinformatics Project team, located in the Computational Biology Branch, is looking for an exceptional candidate with extensive expertise in bioinformatics analysis and biomedical ontology and graph database development to lead the project under the guidance of Dr. Richard H. Scheuermann. This position is located at the NIH main campus in Bethesda, Maryland, U.S.A.
The interdisciplinary project team is dedicated to developing a Cell Phenotype Knowledgebase (CPKB) that will serve as a comprehensive public reference resource for information on cell phenotypes. The team will comprise bioinformatics analysts responsible for developing and implementing statistically rigorous cell type matching approaches, contributing to incremental knowledge growth by assessing the identification of existing and novel cell types, bioinformatics analysts dedicated to creating a FAIR-compliant cell phenotype representational model (a semantic schema) based on OBO Foundry ontologies and related semantic standards, and bioinformatics analysts focused on developing and implementing an extraction, translation, and loading (ETL) protocol to translate processed assay results, including transcriptional biomarkers produced through a standardized machine learning pipeline, and experiment metadata from selected datasets into standardized semantically-structured assertions (SSS assertions) about cell phenotypes for integration into the cell phenotype graph knowledgebase.
The final product will be an open-access reference knowledgebase centered on healthy and diseased cell phenotypes, tailored to meet the diverse needs of the general biomedical research community. Consequently, the position mandates a robust working knowledge of interdisciplinary bioinformatics fields and the ability to collaborate closely with project team members and researchers across NIH. This collaboration is crucial for supporting core discovery use cases and delivering an open-access reference knowledgebase supporting diagnostic biomarker and therapeutic target discovery for the biomedical research community.


The ideal candidate may or may not be a United States citizen.
We are looking for an individual with:
 Strong working knowledge of tools for processing, reporting, and visualizing scientific data, including web-based applications, e.g., JavaScript, Java, Python, C/C++, R/Shiny apps.
 Strong working knowledge of programming languages and environments used in data science, e.g., Python and/or R, as well as associated programming libraries, e.g., NumPy, SciPy, and Bioconductor.
 Strong working knowledge of the Linux operating system as well as software development and deployment tools, e.g., Docker, Git.
 Familiarity with statistical and machine learning methods.
 Experience with tools for single-cell RNA sequencing analysis (CellRanger, scanpy, Seurat, Leiden clustering, UMAP/tSNE).
 Familiarity with taxonomies, ontologies, and controlled vocabularies, including OBO Foundry ontologies, especially the Cell Ontology, Ontology of Biomedical Investigation, and UMLS/MeSH
 Working knowledge of commonly used ontology and terminology development tools (e.g., Protégé, Ontology Lookup Service, Ontology Development Kit)
 Working knowledge of Semantic Web technologies (RDF/s, OWL), query languages (SPARQL) and validation/reasoning approaches and standards.
 Familiarity with deploying, constructing, and querying data systems, including relational database management systems (RDBMS) and non-SQL systems (e.g., Neo4j graph databases, RDF subject-predicate-object triple stores), and SPARQL and Cypher query languages.
 Strong interpersonal and written communication skills, with experience in collaborative cross-functional teamwork, and the ability to maintain relationships and partnerships with institutions and vendors.
 Adeptness in effectively managing and overseeing multiple projects concurrently, showcasing a keen attention to detail and a remarkable capacity to adapt to evolving work requirements.
Education Requirements:
Candidates must hold a PhD and/or MD degree in biomedical science, computer science, or a related field.

Start date

As soon as possible

How to Apply


Richard Scheuermann