Principal Applied Plasma Data Scientist

What you'll do

• Develop and validate ML frameworks for FRC plasma dynamics, including physics-informed, surrogate, and hybrid approaches.
• Integrate models with simulation and diagnostic pipelines; reproduce experimental conditions and analyze model outputs against experiments.
• Collaborate with fusion researchers and communicate findings through reports, presentations, and visualizations.

What they ask for

• PhD in Physics, Engineering, Applied Math, Computational Science, Machine Learning, or a related field, with emphasis on physics-grounded modeling.
• 10+ years of industry or research-lab experience applying machine learning in experimental, simulation-driven, or scientific R&D environments.
• Expertise with physics-informed or physics-constrained ML methods and experience integrating ML with scientific-computing workflows, simulations, or diagnostics.
• Scripting proficiency for data parsing, model analysis, and visualization (MATLAB, Python, or similar); familiarity with magnetic diffusion, circuit coupling, or plasma-dynamics modeling.

Nice to have

• Fortran or HPC exposure is valuable.

Pay

$230K – $270K (base salary)

Tools

differentiable physics, PINNs, surrogate modeling, hybrid physics+ML systems, MATLAB, Python, Fortran, HPC

AI focus

Develop and validate physics-grounded machine-learning frameworks for FRC plasma modeling, including integration with simulations and experimental diagnostics.