The study of energetic particle effects on neoclassical tearing modes (NTMs) is a key area of focus in the current SciDAC-4 Center on Integrated Simulation of Energetic Particles (ISEP). Current strong interest in Machine Learning has stimulated motivation to investigate associated implications for developing a statistical model of NTMs as a possible disruption trigger based on machine learning for real time prediction and control.
PhD in Astrophysics/Plasma Physics
Reporting to: Dr. William Tang [PI of FES-funded 3-year project on “Machine Learning Application to Predictive Studies of Disruptions in Tokamaks] and Co-PI of
SciDAC-4 Center on Integrated Simulation of Energetic Particles (ISEP)
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