Data Scientist II - AI RF​/Remote Sensing

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.

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We are seeking a Data Scientist – AI for Radio Frequency (RF)/Remote Sensing Researcher. This role bridges foundational research and practical implementation to address cutting‑edge challenges in modern communication, remote sensing, and signal processing. Help shape the future of national security and scientific discovery by applying AI/ML to some of the most challenging problems in communications, remote sensing, and signal processing.

In this role, you’ll combine knowledge of RF and sensor physics with hands‑on expertise in developing and deploying advanced AI/ML models. You will work at the intersection of advanced research and operational implementation to deliver mission‑ready solutions.

Key Responsibilities:

• Conduct research and implement AI/ML algorithms for RF signal processing, including but not limited to intelligent spectrum awareness, opportunistic sensing, and adaptive communication systems.
• Apply machine learning and deep learning techniques to improve the analysis, interpretation, and management of RF signals in noisy, dynamic, or contested environments.
• Develop and integrate AI/ML models into RF communication and remote sensing workflows in collaboration with multidisciplinary teams.
• Implement and iterate on novel AI/ML methods to directly address National Security problems.
• Prototype and demonstrate edge implementations of RF AI/ML models on hardware.
• Reproduce and adapt state‑of‑the‑art models, training methods, and digital signal processing components from academic literature with senior technical guidance but minimal examples and/or author code access.
• Maintain awareness of emerging technologies in AI, machine learning, remote sensing, and RF technologies to identify opportunities for technical innovation.

This position is based in either Richland, WA or Seattle, WA and requires an onsite presence.

Minimum Qualifications:

• BS/BA and 2 years of relevant experience
  -OR-
• MS/MA
  -OR-
• PhD

Preferred Qualifications:

• Degree in computer science, engineering, physics, mathematics, or a related field.
• Foundation in the physics and engineering principles of radio frequency (RF) and remote sensing, coupled with practical experience applying these concepts in AI/ML workflows.
• Experience in AI/ML/DL in applied science/research for national security missions.
• Experience in complex‑valued machine learning.
• Familiarity with the current AI/ML research landscape, particularly methods and applications relevant to RF signal processing and remote sensing.
• Experience implementing machine learning and artificial intelligence techniques for communications, signal processing, time series, RF applications.
• Experience developing, training, and testing machine learning models in frameworks like PyTorch.
• Proficiency in Python development and common associated libraries (e.g., pandas,…