Computational Scientist in the Artificial Intelligence for Science (AIScience)
Artificial Intelligence for Science and Energy represents a fundamental change in the scientific enterprise and an opportunity to provide foundational capabilities upon which to broaden PPPL’s mission. The incumbent will build new capabilities in the Computational Sciences Department to leverage this once-in-a-generation opportunity to build an AI4Science research program at PPPL. Specifically, the incumbent will address the emerging need for AI/ML in fusion, other areas of plasma physics, and computational sciences. In addition, the incumbent will work with CSD Leadership to make key hires, build core research capabilities (including training of existing staff), and design a research program to discover new methods in data assimilation, experimental prediction, control systems, and solutions to partial differential equations.
To establish and solicit long-term funding for a program focused on (a) foundational research in Artificial Intelligence and Machine Learning (AI/ML), and (b) application-oriented research in PPPL-relevant AI4Science topics.
The Computational Sciences Department at PPPL was formed to provide a focus for computational physics and engineering. We specialize in algorithms and applied mathematics, data science and learning, high-performance computing, multiscale integrated modeling, and software technology. While our current strengths reflect the traditional focus of the Laboratory on magnetic confinement fusion (MCF), with funding from the Department of Energy’s offices of Fusion Energy Sciences and the Advanced Scientific Computing Research, PPPL has always had a broad and healthy research program in areas other than MCF, including developing the theoretical and computational foundations of the dynamics and thermodynamics of naturally occurring plasmas, and more recently, in AI/ML and AI4Science.
The successful candidate will help develop the laboratory’s effort in AI/ML and AI4Science, collaborating with CSD leadership and other laboratory divisions. The candidate will help establish partnerships with Princeton University and other DOE National Laboratories. The candidate will assist in recruiting new team members, seek and secure funds to support the laboratory team, and present and publish original research in this general area. The present position comes with steady-state funding for three years.
We are looking for candidates who can build a strong research program in one or more of the following topics:
- Machine Learning for Digital Twins, Foundation Models, and surrogates.
- Inference tools for interpretive analysis of experimental and simulation data.
- Foundational research in Machine Learning for partial differential equations (PDEs).
- Innovative algorithmic and methodological approaches to AI-augmented HPC application acceleration.
- Advanced systems and software for AI-augmented High-Performance Computing at scale.
- Machine-learning-driven control systems control large and complex experiments in real-time,to avoid “dangerous” conditions (disruption avoidance) using feedback systems.
- Scalable hybrid AI-HPC workflows using advanced capabilities.
This position requires building close collaboration with CSD Leadership, PPPL experimentists, the PPPL Theory Department, and Princeton University researchers.
A U.S. Department of Energy National Laboratory managed by Princeton University, the Princeton Plasma Physics Laboratory (PPPL) is tackling the world’s toughest science and technology challenges using plasma, the fourth state of matter. With more than 70 years of history, PPPL is a leader in the science and engineering behind the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise to advance research in the areas of microelectronics, quantum sensors and devices, and sustainability sciences. Whether it be through science, engineering, technology or professional services, every team member has an opportunity to contribute to our mission and vision. Come join us!