The engineer will independently develop and deploy AI-enabled methods that combine device physics, measured silicon data, compact-model simulations, and TCAD results to accelerate model extraction, improve predictive accuracy, and create scalable modeling workflows for CMOS, cryogenic, photonic, superconducting, and other emerging devices. Develop, optimize, and validate machine-learning methods for semiconductor device modeling, including parameter extraction, surrogate modeling, model calibration, inverse modeling, and prediction of device characteristics.