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NSIP Undergraduate Intern – Artificial Intelligence & Data Analytics - SWE Conference

Job in Richland, Benton County, Washington, 99352, USA
Listing for: Pacific Northwest National Laboratory
Apprenticeship/Internship position
Listed on 2026-11-05
Job specializations:
  • IT/Tech
    Data Scientist, AI Engineer (Applied/Software), Data Science Manager, Data Analyst
Salary/Wage Range or Industry Benchmark: 17.13 - 27.02 USD Hourly USD 17.13 27.02 HOUR
Job Description & How to Apply Below
Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex,real-world threats to our nation and the world.

The AI and Data Analytics Division, part of the National Security Directorate, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support.

Responsibilities

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The AI and Data Analytics (AIDA) Division, part of the National Security Directorate, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster. Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support.

Read more about the AIDA division at https://www.pnnl.gov/ai-and-data-analytics

PNNL is seeking Undergraduate students for assignments within the National Security Internship Program (NSIP). The AI and Data Analytics Division is looking for individuals who have a passion for solving critical national challenges using advanced computational, statistical, and mathematical techniques. The intern will be given an opportunity to be presented with complex problems in national security, energy, and science; apply cutting‑edge research to make our nation safer and stronger;

develop complex computer code; develop and participate in cyber competitions; design new visualization; work with big data and optimize solutions in diverse domains.

Participants will begin in one of two cohort sessions and must be available to start byand complete the full 10-week program. Cohort 1 runs from May 25 through July 30, and Cohort 2 runs from June 22 through August 27.

Diverse Focus Areas:
Your internship can be in one of six technical groups.

Math, Stats, and Data Science

We employ powerful tools and techniques, such as mathematical modeling and computational statistics, graph and game theory, network science, and uncertainty quantification to solve complex problems in a variety of domains. Disciplines:
Applied Mathematics, Machine Learning, Statistics,…

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