We are seeking an AI/ML Postdoctoral Researcher within our Laser Science and Systems Engineering (LSSE) Program to research cutting-edge machine learning applications for laser performance optimization and modeling on the National Ignition Facility (NIF). NIF is the world’s most energetic laser and home to the team that achieved fusion ignition in December 2022, a historic moment in science that opened new physics regimes and set the stage for new fusion energy possibilities.
This is an exceptional opportunity for a researcher at the intersection of Physics and Artificial Intelligence/Machine Learning (AI/ML) to make immediate, high-impact contributions to NIF operations and projects. You will identify, develop, and deploy AI/ML solutions across a broad spectrum of high-impact applications related to NIF laser performance and modeling. You will work in close collaboration with the Beam Line Integrated Performance (BLIP) team, the LPOM (Laser Performance Operations Model) team, and NIF laser operations teams to ensure innovations translate directly into operational improvements.
This position is in the National Ignition Facility and Photon Science (NIF&PS) Principal Associate Directorate (PAD).
In this role, you will
- Conduct research and development of an inverse pulse solve machine learning system by training, testing, optimizing and deploying ML models (neural networks, gradient boosted trees, ensemble methods) using thousands of historical NIF laser setup calculations.
- Identify and pursue high-impact AI/ML opportunities across the laser program, including laser performance prediction, optimization and anomaly detection, ML-enhanced diagnostic data analysis and trending, and physics-informed neural networks for laser physics modeling.
- Solve abstract and complex problems, using in-depth analysis, and drawing from advanced level technical knowledge, best practices, and both routine and innovative techniques and approaches.
- Collaborate extensively with BLIP, LPOM and NIF laser operations team members to understand operational requirements for ML system development/deployment, validate ML predictions against physics models and experimental results, and integrate ML tools into existing workflows.
- Support and educate team members in the application of scientific AI/ML techniques within a collaborative and dynamic team environment.
- Organize, analyze, and present results through peer-reviewed publications in leading scientific journals, presentations at machine learning and laser physics conferences, internal technical reports and documentation, and regular briefings to stakeholders and NIF leadership.
- Perform other duties as assigned.
- PhD in Applied Physics, Applied Mathematics, Computer Science, or related technical field or discipline.
- Demonstrated expertise in machine learning and data science with experience or coursework in deep learning frameworks (PyTorch, TensorFlow), machine learning methods, model uncertainty quantification (e.g. Bayesian methods), and/or training large-scale models on scientific datasets.
- Proficiency in scientific computing with Python including ML libraries (scikit-learn, XGBoost), numerical computing (NumPy, SciPy, pandas), data visualization (matplotlib, holoviews, plotly), and high-performance computing and parallel processing.
- Experience directing, leading, developing, and executing independent research projects, including publication of peer-reviewed literature.
- Excellent organizational, written and verbal communication, and interpersonal skills to collaborate effectively in a multi-disciplinary team environment and present technical information to various audiences.
Qualifications We Desire
- Solid foundation in physics, with experience or coursework in laser physics, short-pulse and high peak power laser systems, nonlinear optics, frequency conversion, laser-matter interaction, optical propagation, beam physics, wave optics, solid state laser architectures or amplifier physics.
Pay Range
$123,048 Annually
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
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Position Information
This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.
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