The NDSU Center for Computationally Assisted Science and Technology (CCAST), Information Technology Division, is seeking students to join our Internship Program in Advanced Research Computing. Student interns in the researcher-facing track will work on projects related to the application of advanced computing (i.e., high-performance computing (HPC)/supercomputing, high-throughput computing, etc.) and assist researchers in various research areas. 

Undergraduate and graduate students who are in good standing and possess the required qualifications and experience will be considered. We offer training and professional development opportunities for our interns.

Hours Per Week: 10-20 in Spring/Fall, up to 40 in Summer
Starting Wage:  $17/hour or higher, commensurate with experience
Reports To:  CCAST Staff

NOTE: This position could qualify as a graduate assistantship. To be hired as a graduate assistant, the following criteria must be met: 
1) the student is a graduate student eligible for tuition waiver on an assistantship contract
2) the student must work the number of hours agreed upon and specified in the student's Graduate Contract form 

Duties and Responsibilities:

• Educating researchers on proper and efficient use of shared HPC resources
• Building, testing, and optimizing software packages on HPC systems
• Assisting researchers in troubleshooting or optimizing their codes
• Assisting researchers in streamlining their workflows
• Performing other tasks assigned by the CCAST staff

Minimum Qualifications: 

• A full-time NDSU student
• Experience working with UNIX/Linux-based systems and experience using HPC facilities
• Strong communication (written and oral) and interpersonal skills; ability to write clear user instructions and develop tutorials and training materials
• Self-motivation, strong willingness to learn, and strong problem-solving skills

Preferred Qualifications: 

• Experience with software compilation and installation on HPC systems
• Research experience in one or more research areas: biological sciences, computer and information science and engineering, engineering, mathematical and physical sciences, or social, behavioral and economic sciences, etc.
• Experience with parallelism in, e.g. Python, R, or MATLAB, and with numerical libraries (e.g., Intel MKL)
• Experience with one or more programming languages (Fortran, C/C++, Python, or others)
• Experience with parallel programming APIs (OpenMP, MPI, CUDA, OpenACC, etc.)