Senior Data Scientist - AI-Enabled Signal Exploitation

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 NSD, combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytics 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 Senior Data Scientist – AL‑Enabled Signal Exploitation. This role blends basic research and real‑world implementation to solve some of the most complex and cutting‑edge challenges in modern communication and signal processing. The primary focus of this position is the development and implementation of advanced artificial intelligence (AI) algorithms to enhance the performance, security, and efficiency of radio frequency (RF) communication and sensing systems.

• Conduct cutting‑edge research to develop new AI techniques and algorithms for RF signal processing, including but not limited to automatic modulation recognition, signal detection and classification, and adaptive communication systems.
• Apply machine learning and deep learning methodologies to improve the analysis, interpretation, and management of RF signals in noisy and contested environments.
• Collaborate with cross‑disciplinary teams to integrate AI technologies into existing and next‑generation RF communication systems, ensuring they meet stringent security and reliability standards.
• Design, implement, and iterate on novel deep learning methods to directly address National Security problems.
• Ability to recreate state‑of‑the‑art architectures, training techniques, and digital signal processing blocks from journal publications with minimal examples and/or author code access.
• Stay abreast of advancements in AI, machine learning, and RF technologies to identify opportunities for innovation and improvement in national security applications.

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

Minimum Qualifications:

• BS/BA and 5+ years of relevant work experience –OR–
• MS/MA and 3+ years of relevant work experience –OR–
• PhD with 1+ year of relevant experience

Preferred Qualifications:

• Experience in AI/ML/DL in applied science/research for national security challenges
• Experience leading research efforts that apply machine learning and artificial intelligence to communications, signal processing, time series, radio frequency applications
• Experience in Python development and common associated libraries (e.g., Pandas, Numpy, Scipy)
• Experience and proficiency developing, training, and testing machine learning models in frameworks like Py Torch
• Active DOE Q clearance and ability to maintain such clearance
• Active TS/SCI clearance and ability to maintain such clearance
• Strong communication and cross‑functional collaboration skills

Not applicable.

This position requires the ability to obtain and maintain a federal security clearance.

A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your personal references, neighbors, and co‑workers to…