Senior Plasma Data Scientist

About the role

You will own the development and validation of synthetic diagnostic frameworks that bridge experimental measurements with simulation outputs for FRC plasma at Helion. This role centers on building physics-grounded machine learning models that sharpen the interpretation of plasma behavior and diagnostic fidelity. You will own end-to-end responsibility for integrating these models into live experimental and simulation data pipelines in support of rapid analysis cycles. In this position, you will work closely with the Experimental Science Manager at our Everett, WA office to define, test, and refine models that advance the understanding of FRC dynamics. Your work will directly support the interpretation of magnetic diffusion, circuit response, and diagnostic measurements critical to progressing toward fusion electricity. You will own the communication of technical findings to both technical and cross-functional stakeholders through clear reports and visualizations. This is a pivotal role in enabling Helion's path to a scalable, clean, and reliable fusion energy future.

Key facts

What you'll do

• Develop and validate machine-learning frameworks for FRC plasma-dynamics, leveraging physics-grounded ML approaches (e.g., differentiable physics, PINNs, surrogate modeling, or hybrid physics+ML systems).
• Integrate ML models with existing simulation tools and experimental-diagnostic pipelines to enable hybrid physics + data-driven validation workflows.
• Reproduce experimental plasma conditions within ML modeling workflows to support interpretation of magnetic diffusion, circuit response, and diagnostic measurements.
• Generate analysis scripts for post-processing, parsing model outputs, and visualizing correlations between ML-based predictions and experimental results.
• Collaborate with plasma-physics, pulsed-power, and transient-magnetics experts to expand the fidelity and fusion-relevance of ML-enabled modeling frameworks.
• Communicate results with rigor and clarity through reports, presentations, and technical visualizations for research stakeholders.
• Design and implement surrogate models that reduce computational cost while preserving critical physics behavior in FRC experiments.
• Support the creation of automated analysis tools that streamline diagnostic calibration and uncertainty quantification across experimental campaigns.
• Partner with diagnostics and engineering teams to align synthetic diagnostics with hardware measurements and data-quality standards.
• Contribute to the continuous improvement of data-processing pipelines, ensuring reproducibility, scalability, and traceability of analysis results.
• Translate experimental observations into modeling insights that inform plasma control strategies and system-level performance targets.
• Assist in defining validation metrics and benchmarks that align ML outputs with physical expectations and experimental uncertainty.
• Document methodologies, assumptions, and results to support peer review and cross-team knowledge transfer.
• Participate in internal reviews and design discussions to integrate data-driven insights into broader simulation and experimental planning.
• Adapt modeling approaches as new diagnostic capabilities and experimental configurations are introduced at Helion.

Requirements

• PhD in Physics, Engineering, Applied Math, Computational Science, Machine Learning, or related field with emphasis on physics-grounded modeling.
• 3+ 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, such as differentiable physics, PINNs, scientific ML, surrogate modeling, or reduced-order models for complex physical systems.
• Experience integrating ML models with scientific-computing workflows, simulation tools, or experimental diagnostics.
• Proficiency scripting for data parsing, model analysis, and visualization (MATLAB, Python, or similar; Fortran or HPC exposure valuable).
• Familiarity with magnetic diffusion, circuit coupling, or plasma-dynamics modeling in pulsed-power or electromagnetics systems.
• Strong background in statistical modeling, uncertainty quantification, and validation techniques for simulation and experimental data.
• Demonstrated ability to work effectively in a multidisciplinary team environment with experts in plasma physics, pulsed power, and transient magnetics.
• Commitment to rigorous analysis, including clear documentation of methods, assumptions, and limitations in scientific contexts.
• Excellent verbal and written communication skills for presenting technical results to both specialized and general audiences.
• Proven track record of delivering robust, reproducible analysis in complex, data-driven environments.
• Alignment with Helion's mission to build the world's first fusion power plant and operate with urgency, rigor, and ownership.
• Willingness to work from our Everett, WA office and engage with experimental teams on-site as required.

Practical notes

-

Location: Everett, WA

-

Engagement: Full-time

-