Develop a fast AI model for FRC stability in respect to n=1 tilt mode, which can be used to guide large scale nonlinear simulations. Use the HYM code at NERSC to perform a parameter scan and calculate growth rates of the tilt instability in field-reversed configurations (FRCs). Use the generated dataset to develop a machine-learningâ“based surrogate model for predicting the linear stability of FRC equilibria.

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!

Core Duties:

• Organize data from simulations, develop a simple surrogate model using several equilibrium parameters as input, and growth rates calculated in linear simulations for AI model training.

Education and Experience:

• Undergraduate student.

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