Student

St. Jude Children's Research Hospital • Remote - TN, TN

5d

About The Position

We are seeking a motivated and detail-oriented student employee to support the refinement and expansion of a rule-based workload classification framework within our HPC environment. This role will contribute to the development of real-time job tagging, metadata extraction, and advanced classification techniques, and help integrate visualizations into comprehensive dashboard systems.

Requirements

• Currently enrolled in a Bachelor's or Master's program in Computer Science, Data Science, Engineering, or a related field.
• Familiarity with Python and data processing libraries (e.g., Pandas, NumPy).
• Understanding of basic machine learning concepts and classification techniques.
• Experience working with structured and unstructured data.
• Strong analytical and problem-solving skills.
• Ability to work independently and communicate effectively in a team setting.

Nice To Haves

• Experience with job schedulers (e.g., LSF, Slurm, PBS) and HPC environments.
• Knowledge of metadata parsing and log analysis.
• Exposure to data visualization tools (e.g., Plotly, Dash, Grafana).
• Familiarity with dashboard integration and web-based UI frameworks.
• Prior experience with rule-based systems or workflow automation.

Responsibilities

• Enhance rule-based logic for real-time job tagging based on job metadata and runtime characteristics.
• Develop and implement methods for automated extraction of storage locations from job metadata.
• Introduce and evaluate supervised and unsupervised classification models to improve workload categorization.
• Collaborate with team members to integrate classification visualizations into existing dashboard platforms.
• Document processes, findings, and improvements for internal knowledge sharing and future development.

Benefits

• Hands-on experience in a high-performance computing environment.
• Opportunity to contribute to impactful infrastructure and analytics tools.
• Mentorship from experienced professionals in HPC and data science.
• Flexible schedule to accommodate academic commitments.

What This Job Offers

• Job Type: Part-time
• Career Level: Intern
• Education Level: Associate degree