MISM Data and Metadata Intern

Overview

One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community.

University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates for performing arts events.

Are you ready to go beyond the state of the art? At the Renaissance Computing Institute (RENCI), we use data, creativity, and inclusive teaming to revitalize how science is done. Fostering data science expertise and creating cyberinfrastructure isn’t just about solving known problems – it’s about expanding human potential by unlocking data.

We need innovators, builders, strategists, technologists, architects, and creative thinkers across all domains to drive this work forward. When you join our team, you’ll:

• Spend your time solving the interesting and unique problems of research and development.
• Shape your future through experimentation and unfettered access to premier education and research.
• Make connections to people and projects that ignite your passion.

We know that diversity of people and ideas is a cornerstone of innovation, and we work to ensure our culture reflects that knowledge. We provide the tools you need to do your job effectively; we offer flexibility so you can be the most productive version of you; and we encourage thoughtful and challenging discourse.

Join our research institute at the University of North Carolina at Chapel Hill today and help us spark a scientific renaissance across the Research Triangle Park, North Carolina, and beyond.

RENCI is seeking an intern to support the MISM platform effort by helping identify, collect, and organize metadata about relevant biomedical, infectious disease, immunology, and modeling resources. The intern will gather information about datasets, computational models, and related resources from sources such as the NIAID Data Ecosystem, biomedical model repositories, and ontology‑driven standards such as the Biolink Model.

This work will support a proof of concept for constructing a knowledge graph that represents relationships among models, datasets, biological concepts, metadata standards, and ontologies. The resulting knowledge graph will be used to explore integration with CAIRNS semantic search capabilities, with the goal of improving model and data discovery across heterogeneous scientific resources.

The intern will work with the MISM technical team to:

• Identify relevant models, datasets, and metadata sources from NIAID‑related resources and other biomedical data/model repositories.
• Gather structured metadata about models and datasets, including title, description, source, domain area, organism, disease area, data type, model type, inputs, outputs, assumptions, dependencies, licensing, provenance, and access information.
• Review existing metadata and ontology standards relevant to biomedical knowledge graphs, including the Biolink Model, which is designed to standardize biological knowledge graph entities and relationships.
• Help define a practical metadata schema for representing models and datasets in the MISM platform.
• Map collected metadata to controlled vocabularies, ontologies, or knowledge graph predicates where appropriate.
• Assist with documenting how datasets, models, concepts, and ontologies relate to one another.
• Contribute to a small proof‑of‑concept knowledge graph that can be used to test semantic search and discovery workflows.
• Work with RENCI developers and research staff to prepare metadata for integration with CAIRNS semantic search.

By the end of the internship, the intern is expected to contribute to:

• A curated inventory of relevant models, datasets, and biomedical resources.
• A structured metadata spreadsheet, JSON, or similar machine‑readable metadata collection.
• A draft metadata schema for MISM model and dataset discovery.
• Notes comparing relevant metadata and ontology…