Senior Data Scientist III - Machine Learning GEOINT and Remote Sensing

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, Integrated Discovery 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.

PNNL is seeking a Senior Data Scientist III with deep learning expertise to develop methods for detecting and classifying targets in electro-optical (EO) imagery or identifying targets and materials in hyperspectral imagery (HSI). This research supports geospatial intelligence (GEOINT) and national missions.

In the AI and Data Analytics Division, you will lead research projects or major parts of larger projects, developing methods from initial ideas through evaluation and integration into research prototypes.

Current priorities include automatic target recognition (ATR), long-wave infrared (LWIR) HSI target detection and material classification, and detection and classification with limited labeled training examples, particularly in EO imagery. The role also offers opportunities to explore related problems in remote sensing and intelligence analysis. Candidates with deep learning experience in EO, HSI, or related sensing applications are encouraged to apply.

You will work alongside researchers and domain specialists on difficult national science and technology challenges. Collaboration with software and machine learning (ML) engineers will reflect each project's needs and stage of development. Opportunities to advance existing research and pursue new ideas may come through ongoing projects, internal research investments, or new proposals.

• Develop and adapt detection and classification methods through algorithm development, mathematical analysis, experimentation, or implementation.
• Lead research projects or major technical efforts, coordinate contributors, and plan the work, resources, and milestones.
• Evaluate methods against appropriate baselines using representative data. Investigate classification errors, false alarms, robustness, and limitations that affect their use.
• Build and validate research prototypes with software and ML engineers, addressing technical barriers to integration and deployment.
• Work with collaborators to turn mission or user needs into research questions, and communicate findings through analyses, technical reports, and discussions.
• Develop research ideas and collaborate with project leaders on proposals to support your research.
• Mentor colleagues, help recruit and onboard researchers, and share methods and findings across disciplines.
• Follow applicable quality, safety, and security requirements.

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

Minimum Qualifications:

• BS/BA and 5+ years of data science experience
  -OR-
• MS/MA and 3+ years of data science experience
  -OR-
• PhD with 1+ year of data science experience
• Experience applying and evaluating deep learning methods for detection and classification in electro-optical (EO) imagery or target detection and material classification in hyperspectral imagery (HSI).
• Experience developing deep learning methods using PyTorch or another deep learning framework.

Preferred Qualifications:

• Experience with the EO or HSI imaging chain, including sensor response, image formation, calibration, and data processing. LWIR HSI experience is particularly valued.
• Experience in addressing limited labeled training data or new target categories through methods such as few-shot learning,…