Blacksburg, VA30+ days ago
Candidates may focus on one or more domains such as semiconductor devices and nanomanufacturing, process control, yield learning, variability, reliability, photonics and optoelectronics, inverse design, fabrication-aware modeling, nonlinear or multi-physics systems, quantum and cryogenic platforms, noise modeling, calibration, control, materials-device coupling, wireless and sensing systems, AI-native PHY/MAC RF-aware learning, joint sensing-communications, power electronics and power systems, physics-aware grid modeling, stability, protection, resilience, microgrids, and cross-domain work that transfers Physical AI methods across platforms. The successful candidate will develop AI-native models, digital twins, and control frameworks that bridge the loop between theory, simulation, experimentation, and deployment across one or more of ECEs core strength areas, including: • Semiconductors and micronanofabrication • Photonics and optoelectronics • Quantum and cryogenic devices • Wireless communications, networking, and sensing systems • Power electronics, power systems, and energy infrastructure.