The turbulence spectroscopy group in the Department of Engineering Physics has an immediate opening for a postdoc or early-career scientist in machine learning (ML) and real-time inference for Beam Emission Spectroscopy (BES) plasma turbulence measurements at the DIII-D National Fusion Facility. The appointee will develop neural networks for real-time data analysis on high-throughput FPGA or GPU accelerators with targeted applications for real-time ELM (edge localized mode) onset prediction and pedestal turbulence/instability characterization. The project is part of a multi-institution collaboration for ML-enhanced plasma control. Applicants with experience in deep learning, data acquisition instrumentation, and fusion data analysis for turbulence and instabilities are encouraged to app