Collaborate with a biomedical ontologist to develop a FAIR-compliant cell phenotype semantic schema based on OBO Foundry ontologies and an extraction, translation, and loading (ETL) protocol for translating processed assay results and experiment metadata from sc/snRNA-seq datasets into semantically-structured assertions about cell phenotypes for loading into a graph knowledgebase; integrate cell phenotypes with disease, drug, and other information from external public graph knowledgebases (e.g., SPOKE) to facilitate mechanistic, diagnostic, and therapeutic use cases; develop and implement intuitive user-friendly query, visualization, and analysis interfaces for semantic network exploration.
• PhD and/or MD degree in a biomedical science, computer science or related field.
• Strong working knowledge of deploying, constructing, and querying data systems, including graph databases (e.g., Neo4j and RDF subject-predicate-object triple stores), SPARQL and Cypher query languages, and validation/reasoning approaches and standards.
• Experience working with taxonomies, ontologies, and controlled vocabularies, including OBO Foundry ontologies, especially the Cell Ontology, Ontology of Biomedical Investigation, and UMLS/MeSH.
• Familiarity with programming languages & environments used in data science, e.g., Python and/or R and associated libraries, e.g., numpy, scipy, and bioconductor.
To Apply: Candidates should send the following application materials directly to Dr. Richard H. Scheuermann at rscheuermann@jcvi.org and copy Dr. Virginia Meyer at virginia.meyer@nih.gov :
• Current curriculum vitae
• Cover letter/statement of research interest
• Contact information for three references