PNNL's AI and Data Analytics Division is seeking PhD students to address complex data and analytic challenges in national security, energy, and science by applying advanced computational, statistical, and mathematical techniques.
Requirements
- mathematical modeling
- computational statistics
- graph and game theory
- network science
- uncertainty quantification
- Artificial Intelligence
- Applied Machine Learning
- Data Science
- Deep Learning
- Computer Vision
- Geospatial Intelligence
- Natural Language Processing
- Cloud Engineering
- Large-Scale Data Engineering
- Scalable Machine Learning/Artificial Intelligence
- DevSecOps
- Automated Testing
- Software Engineering
- Human-Computer Interaction
- User Experience
- Graph Analytics and Data Visualization
Responsibilities
- develop complex computer code
- develop and participate in cyber competitions
- design new visualization
- work with big data and optimize solutions in diverse domains
- develop hardened and robust models to distill large, fast, distributed, and messy data into knowledge to support decision processes in operational environments on sponsor systems
- conceptualize and develop fundamentally new algorithms and tools to address unresolved challenges in distilling large, fast, distributed, and messy data into knowledge to support sponsors’ decision processes
- develop high-quality, scalable, cloud-first solutions for tackling large data pipelines and analytics that are delivered to operational sponsor environments
Other
- Candidates must be currently enrolled/matriculated in a PhD program at an accredited college.
- Minimum GPA of 3.3 is required.
- U.S. Citizenship is required.
- Participants will be starting in cohort sessions and must be available to start in May or June 2026.
- Positions are available in Richland, WA and Seattle, and Sequim WA, based on business need. Positions may also be performed remotely or on campus at PNNL based on business need.
