Graduate Summer Intern – I/O optimization for data-intensive workflows on HPC
National Laboratory of the Rockies, Golden, CO, United States
Graduate Summer Intern – I/O optimization for data-intensive workflows on HPC
Location: CO - Golden
Position Type: Intern (Fixed Term)
Hours Per Week: 40
About the Laboratory
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado and is the nation's primary laboratory for energy systems research and development. It focuses on advanced research and analysis, integrating multidisciplinary teams and collaborating with industry, academia, and other national laboratories to innovate in energy solutions.
Job Description
The Advanced Computing Solutions Group in the NLR Computational Science Center has an opening for a graduate student researcher in HPC with special emphasis on workflow I/O optimization. I/O operations on HPC systems frequently emerge as key performance bottlenecks, turning data storage and movement into a major challenge. The intern will help evaluate the performance and efficiency of I/O operations within scientific computing workflows. This project will examine the I/O behavior of representative NLR problems such as resource estimation (reV) and AI/ML training/inference based on spatial data with the goal of improving the throughput of data movement.
We are looking for a dynamic, motivated researcher with a strong technical background and an interest in the mission of NLR. The successful candidate will collaborate with NLR staff and researchers to optimize the performance of scientific workflows in HPC.
Responsibilities
Familiarize yourself with the NLR flagship datasets (e.g. WTK, NSRDB, Sup3rCC) and scientific workflows that utilize them.
Understand and leverage software frameworks to analyze the storage structure in NLR HPC systems: parallel file systems, Lustre, Progressive File Layouts, HDF5 chunking, etc.
Collaborate with NLR researchers to utilize profiling tools (e.g., Darshan) to analyze I/O footprint of scientific workflows: random and contiguous reads/writes, latency and throughput, metadata operations.
Design and create representative I/O benchmarks.
Process and visualize the profiling results to suggest and implement I/O improvements.
Author, present, and assist in the preparation of technical papers, reports, and conference proceedings on topics related to HPC storage and data movement.
Basic Qualifications
Minimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full‑time student in a bachelor’s degree program from an accredited institution.
Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full‑time student in a master’s degree program from an accredited institution.
Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.
Preferred Qualifications
Demonstrated programming experience in multiple languages such as Python and/or Julia on Unix/Linux systems.
Demonstrated experience in Shell scripting and Conda/Jupyter use.
2+ years experience using PyTorch or Tensorflow or a related AI/ML framework.
Demonstrated experience working with large data sets (e.g., CFD outputs, NSRDB, WTK, etc.) and interfaces for science applications, including data processing and analysis tools.
Familiarity with HPC profiling and benchmarking tools, such as Darshan and OSU MPI Test Suite.
Experience with high‑performance computing, distributed computing, and related technologies.
Ability to quickly learn new programming languages and frameworks and adapt to changing research demands in a fast‑paced scientific environment.
Demonstrated experience developing workflows, including job scheduler integration, data management of large datasets, data movement, and data availability/sharing with remote users and systems.
Annual Salary Range (Full‑time 40 hours per week)
$44,500 - $71,200 (based on education, experience, travel, market and internal alignment).
Benefits Summary
Medical, dental, and vision insurance.
403(b) Employee Savings Plan with employer match.
Sick leave (where required by law).
Possible eligibility for performance‑, merit‑, and achievement‑based awards with monetary component (not guaranteed).
Possible eligibility for relocation expense reimbursement.
Note: Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. Employees must obtain and maintain a federal Personal Identity Verification (PIV) card and a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.
Drug‑Free Workplace
NLR maintains a drug‑free workplace in compliance with federal law. A pre‑employment drug test is required prior to commencing employment, and the policy applies to all employees.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, or any other protected status.
E‑Verify
E‑Verify is used to confirm the eligibility to work in the United States. For more information, visit www.dhs.gov/E-Verify.
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Location: CO - Golden
Position Type: Intern (Fixed Term)
Hours Per Week: 40
About the Laboratory
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado and is the nation's primary laboratory for energy systems research and development. It focuses on advanced research and analysis, integrating multidisciplinary teams and collaborating with industry, academia, and other national laboratories to innovate in energy solutions.
Job Description
The Advanced Computing Solutions Group in the NLR Computational Science Center has an opening for a graduate student researcher in HPC with special emphasis on workflow I/O optimization. I/O operations on HPC systems frequently emerge as key performance bottlenecks, turning data storage and movement into a major challenge. The intern will help evaluate the performance and efficiency of I/O operations within scientific computing workflows. This project will examine the I/O behavior of representative NLR problems such as resource estimation (reV) and AI/ML training/inference based on spatial data with the goal of improving the throughput of data movement.
We are looking for a dynamic, motivated researcher with a strong technical background and an interest in the mission of NLR. The successful candidate will collaborate with NLR staff and researchers to optimize the performance of scientific workflows in HPC.
Responsibilities
Familiarize yourself with the NLR flagship datasets (e.g. WTK, NSRDB, Sup3rCC) and scientific workflows that utilize them.
Understand and leverage software frameworks to analyze the storage structure in NLR HPC systems: parallel file systems, Lustre, Progressive File Layouts, HDF5 chunking, etc.
Collaborate with NLR researchers to utilize profiling tools (e.g., Darshan) to analyze I/O footprint of scientific workflows: random and contiguous reads/writes, latency and throughput, metadata operations.
Design and create representative I/O benchmarks.
Process and visualize the profiling results to suggest and implement I/O improvements.
Author, present, and assist in the preparation of technical papers, reports, and conference proceedings on topics related to HPC storage and data movement.
Basic Qualifications
Minimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full‑time student in a bachelor’s degree program from an accredited institution.
Post Undergraduate: Earned a bachelor’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full‑time student in a master’s degree program from an accredited institution.
Post Graduate: Earned a master’s degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.
Preferred Qualifications
Demonstrated programming experience in multiple languages such as Python and/or Julia on Unix/Linux systems.
Demonstrated experience in Shell scripting and Conda/Jupyter use.
2+ years experience using PyTorch or Tensorflow or a related AI/ML framework.
Demonstrated experience working with large data sets (e.g., CFD outputs, NSRDB, WTK, etc.) and interfaces for science applications, including data processing and analysis tools.
Familiarity with HPC profiling and benchmarking tools, such as Darshan and OSU MPI Test Suite.
Experience with high‑performance computing, distributed computing, and related technologies.
Ability to quickly learn new programming languages and frameworks and adapt to changing research demands in a fast‑paced scientific environment.
Demonstrated experience developing workflows, including job scheduler integration, data management of large datasets, data movement, and data availability/sharing with remote users and systems.
Annual Salary Range (Full‑time 40 hours per week)
$44,500 - $71,200 (based on education, experience, travel, market and internal alignment).
Benefits Summary
Medical, dental, and vision insurance.
403(b) Employee Savings Plan with employer match.
Sick leave (where required by law).
Possible eligibility for performance‑, merit‑, and achievement‑based awards with monetary component (not guaranteed).
Possible eligibility for relocation expense reimbursement.
Note: Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. Employees must obtain and maintain a federal Personal Identity Verification (PIV) card and a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.
Drug‑Free Workplace
NLR maintains a drug‑free workplace in compliance with federal law. A pre‑employment drug test is required prior to commencing employment, and the policy applies to all employees.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, or any other protected status.
E‑Verify
E‑Verify is used to confirm the eligibility to work in the United States. For more information, visit www.dhs.gov/E-Verify.
#J-18808-Ljbffr