Senior Plasma Control Engineer

Plasma control algorithms and real-time software:

Develop, test, and iterate plasma control algorithms for Eos PCS, including multi-rate feedback, supervisory logic, and constraint handling.

Build AI/ML assisted control modules, such as learning-augmented MPC, reinforcement learning in simulation, physics-based models augmented with data-driven corrections, and adaptive control and auto-tuning across operating conditions

Develop and deploy real-time state estimation and multi-diagnostic data fusion to produce control-grade plasma state, including robust profile reconstruction and regime indicators suitable for closed-loop operation.

Develop anomaly detection and early-warning indicators across plasma and plant signals, with clear thresholds and graded mitigation actions.

Partner with plasma physicists to translate physics goals into control objectives, observables, constraints, and validation tests.

Digital twins and modeling:

Design and maintain digital twin models for plasma control loops and coupled plant subsystems, enabling simulation, optimization, and controller development and validation.

Build model validation workflows, including post-shot reconstruction, scenario sweeps, sensitivity studies, and uncertainty-aware comparisons against experimental data

Data and integration:

Build and maintain data pipelines for time-series control and diagnostic data, including labeling, archiving, and training and inference workflows.

Integrate algorithms into the control stack in collaboration with EECS, ensuring compatibility with real-time constraints and low-latency inference where needed.

Maintain high software quality: version control, test coverage, reproducible environments, and operational readiness documentation.