Undergrad Tech Intern - Research Computing Internship (PEARC)

** Overview*
* At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our directorates related to Mission Support & Operations include Office of General Counsel, Business Services, Communications and External Engagement, Operational Systems, Communications and Information Technology, and Performance Management.

At PNNL, our Computing and Information Technology organization is redefining how we work and innovate by reimagining the digital workplace. We empower research and streamline operations-making both faster, smarter, and more efficient-so our professionals can tackle some of the world's toughest challenges in science, energy, and national security. Our experts in AI, cybersecurity, design, and engineering work side by side, using real-time insights and human-centered design to break down barriers.

Ready to make your mark on tomorrow? Come work with us.

Research Computing empowers researchers by removing technical barriers to discovery. We provide access to cutting-edge resources, including high-performance computing (HPC), GPU-accelerated compute, scientific software, research data management (featuring the PNNL Research Library), and cloud computing. Through events like Tech Fest, which brings staff together to showcase projects and discuss new research possibilities, we cultivate a vibrant culture of computing and drive interdisciplinary collaboration to advance computationally enabled science.

** Responsibilities*
* Research Computing at Pacific Northwest National Laboratory (PNNL) empowers researchers by removing technical barriers to discovery. We provide access to high-performance computing (HPC), GPU-accelerated compute, scientific software, research data management (featuring the PNNL Research Library), and cloud computing. We sit within the Computing and Information Technology directorate, which supports PNNL's mission across science, energy, and national security.

Program Overview

This is a cohort-based internship program. Interns work in small teams, each paired with mentors and project stewards from across the Lab. Assignments run 10 to 12 weeks with the possibility of extension. Participants will be starting in cohort sessions and must be available to start in May or June 2027.

The program includes:

+ Strategically important projects with real deliverables in a team environment

+ Weekly engagement with senior leadership, including briefings and a final presentation to our Directorate

+ A dedicated full-time mentor, coaching sessions, workshops, and Lab tours

+ Exposure to diverse career paths in research computing through collaboration with research scientists, engineers, and leadership

+ Social and networking events throughout the program

Project Areas

Intern teams are assigned to projects based on skills and interests. Examples from previous cohorts:

+ Implementing open-source ML workflow tools to enable research teams to automate and leverage ML platforms

+ Prototyping private Generative AI environments to explore how these technologies can transform research processes

+ Optimizing and parallelizing scientific codes for supercomputers, including participation in a high-performance coding bootcamp

+ Building cloud "blueprint" templates on AWS, Azure, and GCP to help scientists and engineers provision cloud services

+ Developing CI/CD pipelines and supporting application migration with software engineering teams

What We Are Looking For

We are recruiting across three tracks. You do not need to fit all three; identify the one that best matches your coursework and interests.

Software Development Track

+ Coursework or project experience in one or more of:
Python, C, C#, JavaScript, React, or R

+ Interest in building tools, APIs, or applications that support scientific research

Data Engineering Track

+ Coursework or project experience in one or more of:
Python, R, SQL, or data pipeline concepts

+ Interest in research data management, ML workflows, or analytics infrastructure

IT / Cloud Engineering Track

+ Familiarity with…