The Renaissance Computing Institute at the University of North Carolina at Chapel Hill (RENCI) is seeking a talented individual for the position of Scientific Applications Developer, to develop software solutions using semantic technologies to facilitate integration and exploration of scientific data. The candidate will primarily support the NSF-funded Phenoscape Project, which provides an ontology-driven knowledge base allowing computation across evolutionary phenotypic descriptions (http://kb.phenoscape.org/). Phenoscape aims to develop APIs which support deep integration of the knowledge encoded in community-developed ontologies into standard scientific analyses. The incumbent will work closely with other team members in designing and implementing new features, as well as evolving and maintaining the core functionality to improve scalability and performance.
– Develop and extend APIs on top of graph databases and/or RDF triplestores
– Implement algorithms that integrate logical and probabilistic inference over biological data
– Devise methods that allow expressive queries to be executed efficiently
– Maintain pipelines for data ingestion and consistency testing
– Assist with developing scholarly publications related to work
– Participate in related activities at RENCI
Relevant post-Baccalaureate degree required; will accept a relevant undergraduate degree and 3 or more years of relevant experience in substitution.
Qualifications and Experience:
– Demonstrated experience in application development using using programming languages commonly used in scientific application development, such as Java or Python
– Good communications skills and experience working in a collaborative, team environment
– Knowledge of ontology and knowledge engineering frameworks and related APIs (OWL API, Jena, SPARQL)
– Experience with Scala or other functional programming languages
– Prior experience with open source software development; integrating a variety of open source libraries
– Experience with Unix-like operating system administration at any level
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