Post Masters Research Associate - AI for Scientific and Energy Systems

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 Physical and Computational Sciences Directorate's (PCSD’s) strengths in experimental, computational, and theoretical chemistry and materials science, together with our advanced computing, applied mathematics and data science capabilities, are central to the discovery mission we embrace at PNNL. But our most important resource is our people—experts across the range of scientific disciplines who team together to take on the biggest scientific challenges of our time. 

The Advanced Computing, Mathematics, and Data Division (ACMDD) focuses on basic and applied computing research encompassing artificial intelligence, applied mathematics, computing technologies, and data and computational engineering. Our scientists and engineers apply end-to-end co-design principles to advance future energy-efficient computing systems and design the next generation of algorithms to analyze, model, understand, and control the behavior of complex systems in science, energy, and national security.

Responsibilities

• Data Preparation & Analysis: Clean, transform, and integrate structured and unstructured datasets and documents, including equipment datasheets and ArcGIS-based spatial data, from environmental and energy systems domains.
• Power Grid Systems, Simulation & Resilience: Knowledge of power grid systems and resilience, with experience applying agentic AI to model power grid simulations, analyze grid-related problems, and support more efficient and reliable operational decision-making.
• Data Engineering & Pipeline Architecture: Design scalable data systems (ETL, data lakes, data meshes) that support large-scale legislation, regulatory, and legal document workflows.
• Software Engineering & DevOps: CI/CD, testing, version control, and open-source practices enabling reliable, reproducible systems across research and production.
• Computer Vision & Image Analysis: Develop and apply computer vision methods for crystallography workflows and metadata processing, including image analysis, object detection, tracking, segmentation, and automated interpretation, to enable automation of light source beamline operations in scientific and real-world environments.
• Generative AI & Foundation Models: Development and evaluation of large-scale generative AI systems, including fine-tuning, agents, tool use, and optimization for robustness, alignment, and efficiency. 
• Agentic AI Systems & Autonomous Workflows: Design and deploy scalable agentic AI systems with autonomous workflows, dynamic tool use, and complex decision-making to support advanced scientific and operational tasks.

Qualifications

Minimum Qualifications:

• Candidates must have received a Master’s degree within the past 24 months or within the next 8 months from an accredited college or university.

Preferred Qualifications

• Masters degree in Computer Science, Data Science, Applied Mathematics, Electrical Engineering, Computational Engineering, or a closely related field.
• Prior research experience, including internship experience within a national laboratory setting.
• Experience in data preparation, integration, and applications involving large language models.
• Strong technical computing skills in Python, with proficiency in NumPy or similar scientific computing frameworks.
• Ability to translate ambiguous or evolving technical objectives into clear, actionable analytical approaches.
• Experience working in applied research settings or collaborative R&D environments.
• Demonstrated ability to work effectively within interdisciplinary and geographically distributed teams, using a collaborative and solutions‑oriented approach.

Hazardous Working Conditions/Environment

Not Applicable.

Testing Designated Position

This is not a Testing Designated Position (TDP).

About PNNL

Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules. PNNL is located in eastern Washington State—the dry side of Was