Student Assistant III

University Corporation for Atmospheric Research•Boulder, CO

1d•$50,585 - $50,585

About The Position

The Computational and Information Systems Laboratory (CISL) seeks a curious, hands-on student to work with experienced engineers on experimental supercomputing systems, including GPU-based hardware, and evaluate technologies that may shape next-generation computing for NCAR’s scientific community. This learning-by-doing role offers real technical problems, mentorship, and opportunities to develop practical skills. This is a one-year term position supporting the deployment, maintenance, and optimization of high-performance computing (HPC), storage, networking, and software systems used for atmospheric and Earth science research. Depending on the candidate’s skill set, the student will collaborate with High Performance Computing Division (HPCD) staff on research and development lab environments and assist with installing, administering, benchmarking, and troubleshooting HPC hardware, operating systems, and specialized software. Other opportunities may include tuning storage and batch schedulers, running analytics, porting NCAR applications to experimental architectures such as GPU environments, and receiving mentorship training to work with junior HPC students and interns. The student must be enrolled and maintain student status for the entire one-year term, or intend to enroll in the next regular session as specified in the education requirement. Student Assistants may not work more than 1,000 hours in any 12-month period. The updated hourly rate is $24.32.

Requirements

Must be enrolled for the entire duration of the appointment, or intend to enroll in the next regular session, for credit in an accredited secondary or postsecondary school, college or university, or qualifying trade school.
Knowledge and understanding of computer, storage, and networking system components.
Ability to work with a team and convey technical concepts to management and senior engineers.
Excellent oral and written communication skills.
Skill in organizing and prioritizing assignments.

Nice To Haves

Experience with fundamental software and systems engineering concepts and practices.
Experience with at least one portable scripting language such as Python or Bash.
Experience with at least one GNU/Linux distribution.
Familiarity with scientific visualization.
Familiarity with open-source software development and distribution.
Familiarity with AI/ML/DL.
Familiarity with GPGPU programming.
Ability to mentor and train students and visitors.

Responsibilities

Gain experience with user application code on existing and new hardware and software technologies.
Learn to support software products, system administration tools, and monitoring utilities to maximize the availability and flexibility of experimental HPC systems.
Work with mentors to develop tools and analytics or enhance existing tools, analytics, and software subsystems for the experimental HPC environment.
Test and evaluate new computing, storage, and networking technologies, associated software stacks, and potential applications for NCAR applications.
Develop knowledge of emerging technologies and how they might enhance the NCAR user experience.
Assist with preparing and delivering technical reports and presentations on research findings.
Assist with writing and presenting recommendations to HPCD management regarding HPC hardware and software products, configurations, and functional enhancements or upgrades.
Propose, research, design, and implement projects, tools, or process improvements that benefit the team and environment.
Learn basic systems administration and maintenance of multi-vendor open-source HPC systems.
Monitor experimental HPC systems routinely and periodically to help ensure proper and efficient operation for stakeholders.
Help plan and execute installations and upgrades to multi-vendor HPC software systems.
Depending on skills and opportunities, assist with HPC lab maintenance, system installation and administration, benchmarking, troubleshooting, storage and batch-scheduler tuning, analytics, and porting applications to experimental architectures.