CISL is excited to announce the arrival of the 2026 cohort for the Summer Internships in Parallel Computational Science (SIParCS) program. 

 

This year, 14 talented students from various universities and academic backgrounds across the country will spend the summer at the Mesa Lab in Boulder, Colorado, working on cutting-edge computational and data science projects.

 

SIParCS logo

The Summer Internships in Parallel Computational Science (SIParCS) program is hosted by NSF NCAR's Computational and Information Systems Lab (CISL).

The interns will be in Boulder from Monday, May 18 through Friday, July 31. Their first in-person day will include an on-site welcome and lunch at the Mesa Lab, followed by a communication planning session in the afternoon.

 

This year, the SIParCS program is partnering with two other key NSF NCAR intern programs: 

  • NESSI—NSF NCAR Earth System Science Internship, hosted by EdEC, NSF NCAR’s Education, Engagement and Early-Career Development division; and

  • NSF SOARS—NSF Significant Opportunities in Atmospheric Research and Science.

This collaborative effort aims to provide a more consistent and robust orientation experience for all interns across NSF NCAR, UCAR, and UCP. The comprehensive orientation will occupy a significant portion of the first week. 

 

The 2026 SIParCS project list, below, showcases the versatility of the student interns. The cohort will work on a fascinating array of projects, engaging with the latest tools and techniques in computational science, machine learning, and data engineering. 

 

The students and their projects are:
 

  • Anna Scribner (North Seattle College)—Natural Language Discovery of NSF NCAR Scientific Data
     
  • LJ Dunphy (Florida State University)—AI Weather and Atmospheric Chemistry Prediction with Physical Constraints
     
  • Ira Ranjan (Plymouth State University)—FastOSSE: A new tool for optimizing ocean observing networks
     
  • Dusti Johnson (Washburn University)—Data Pathfinders: A GDEX UX/UI Intern Quest
     
  • Max Jessey (Tennessee Technological University)—Learning to Fight Wildfires: Reinforcement Learning for Fire Suppression in a Forest Fire Model
     
  • Ethan Campbell (University of North Carolina at Charlotte)—AI Nowcasting Models for Predicting the Evolution of Convective Storms
     
  • Tri Nguyen (Indian University, Bloomington)—CIRRUS - Developing Workflows for Validating Cloud Native Deployments
     
  • Obin Sturm (University of Southern California)—Simulating atmospheric chemistry with MUSICA in Julia
     
  • Nathan Bartley (Texas Tech University)—Improving the code infrastructure of the NCAR air quality sampling drone system
     
  • Xin Guan (The Ohio State University)—Improving Uncertainty Estimates in Earth System Prediction with DART
     
  • Pouya Shaeri (Arizona State University)—OpenIoTwx Dynamic AI-Mesonet, Edge Computing, and Cyber Infrastructure Integration
     
  • Liam Thompson (University of Oklahoma)—Generalized framework for the evaluation and comparison of atmospheric chemistry models with observations
     
  • Riley Fisher (University of Colorado Boulder)—Developing a Mini-App with the JAX Python Library and/or Rust Programming Language
     
  • Gabrielle Forbes (West Chester University)—CISL Outreach, Workforce Development, Education (CODE)

Watch this space! Detailed project descriptions are coming soon.