Data Science / Computer Engineering Summer Internship

Position Overview

The U.S. Army Research Laboratory Army Research Directorate, DoD Supercomputing Resource Center conducts research critical to the Army’s assured land power dominance into the deep future. They work with emerging computational platforms, advanced algorithms, data‐intensive analysis workflows, and immersive visualization tools using high performance computers, emerging processors, development platforms, and a mixed‐reality visualization lab.

Project: Two student interns are sought to develop a distributed processing and analysis pipeline for efficiently analyzing heterogeneous test data. Under the guidance of a mentor, you will engage with domain scientists to learn about test data, existing workflows on HPC resources, and current software stacks. You will design and implement scalable analytical workflows: one intern will prototype configurations (including aspects like the Spark processing engine, HPC vs PSF orchestration, and analytical model implementations) while the other will enhance the tool stack with generalized models, data exploration, explainable machine learning, and containerized services. You will then collaborate to integrate and evaluate the combined solution for performance and future recommendations.

Location: APG, Maryland. Anticipated start date is June 2023 (exact dates to be determined), and this is a summer research appointment which may be extended based on funding, project needs, program rules, and participant availability.

Key Responsibilities

• Meet with domain scientists to understand the test data, current workflows, and software stack used on HPC resources.
• For Intern #1: Prototype scalable analytical workflows on HPC systems by exploring configurations (e.g., Spark processing engine, orchestration on HPC nodes vs PSF) and implementing one deployment setup.
• For Intern #2: Enhance the tool stack by generalizing models, exploring broader feature sets, developing explainable machine learning models, and containerizing services.
• Collaborate to integrate the prototypes, evaluate both model and runtime performance, and provide recommendations for future model design and deployment.
• Utilize HPC resources (Chessie, Jean, and ATC’s DHPI Prometheus) to support big data analytics and service containerization.

Benefits & Perks

• Stipend: To be determined by the sponsor, based on academic standing, discipline, experience, and location.
• Health Insurance Supplement: Participants are eligible to purchase health insurance through ORISE.
• Relocation Allowance
• Training and Travel Allowance