The Content Enrichment Center (CEC) seeks a Knowledge Representation Specialist for developing Elsevier Merged Medical Taxonomy (EMMeT) as part of its Health Sciences Smart Content initiative. The candidate will be responsible for enhancing EMMeT to improve its application in search and discovery products such as ClinicalKey in three key areas:
(re)modeling parts of the ontology
integrating new reference vocabularies or updating EMMeT with newest versions of reference vocabularies
creating cross-walks between EMMeT and other vocabularies.
The candidate will apply own medical knowledge and/or work with external clinical experts to confirm and validate clinical accuracy of EMMeT as both a taxonomy and ontology and will also work with a team of Knowledge Representation Specialists, as well as product leads to determine how to best build and leverage semantic capabilities.
Knowledge of ontology modeling is a must, experience with medical vocabularies such as SNOMED CT and ICD-10 is beneficial.
Qualifications | General Knowledge and Technical Skills
- Proven expertise in building and maintaining a taxonomy/ontology within the medical domain
- Experience in knowledge modeling and ontology management, RDF, OWL
- Scripting skills (Perl, Python,
- Querying skills (MySQL/Oracle, SPARQL)
- Ability to support multiple projects simultaneously and efficiently; ability to manage priorities and time and meet firm deadlines.
Required Education and Experience:
- Medical knowledge through clinical education, training or work experience
- Informatics degree or extensive experience in semantic technologies, including text mining, ontology management and/or linguistics
- Extensive experience with standard medical vocabularies and crosswalks including ICD, SNOMED, MeSH, UMLS, and others
- Health Science-related degree preferred (i.e., MD, NP, PA, RN, PharmD)