MISM Data and Metadata Intern

Department

Renaissance Computing Inst - 637100

Career Area

Research Professionals

Posting Open Date

05/22/2026

Application Deadline

05/27/2026

Position Type

Temporary Staff (SHRA)

Position Title

MISM Data and Metadata Intern

Position Number

20076510

Vacancy ID

S027506

Full-time/Part-time

Full-Time Temporary

Hours Per Week

40

Work Schedule

Monday- Friday, 8:00 AM – 5:00 PM

Position Location:

North Carolina, US

Hiring Range

$12.00 - $24.00 per hour

Estimated Duration Of Appointment

6 months not to exceed 11 months

Be a Tar Heel!:

A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities. Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn.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.

Primary Purpose Of Organizational Unit

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.

Position Summary

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. ([biolink.github.io]1)
• 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 standards, including Biolink and other biomedical ontology resources.
• Example mappings between collected metadata fields and knowledge graph concepts.
• Documentation describing how the collected metadata could support knowledge graph construction and semantic search.
• A small proof-of-concept dataset suitable for use in a MISM/CAIRNS semantic search demonstration.
  
  

The Intern Will Gain Experience With

• Metadata curation for biomedical models and datasets.
• Ontology-informed data modeling.
• Knowledge graph design for scientific discovery.
• FAIR data and model discovery principles.
• Semantic search workflows.
• Research cyberinfrastructure development in a collaborative software engineering environment.
  
  

Minimum Education And Experience Requirements

Demonstrated possession of the competencies necessary to perform the work.

Management Preferences

• Interest in biomedical data, computational modeling, infectious disease, immunology, or translational science.
• Familiarity with metadata standards, ontologies, controlled vocabularies, semantic web concepts, or biomedical data frameworks (e.g., FAIR principles, schema.org, Biolink Model, LinkML).
• Comfort working with structured data formats or graph-based data models, including CSV, JSON, YAML, RDF, or knowledge graphs.
• Ability to read scientific or technical documentation or extract structured information.
• Experience with Python or other data wrangling tools
  
  

Campus Security Authority Responsibilities

Not Applicable.