Postdoctoral Scholar

Lawrence Berkeley National Laboratory is hiring a Postdoctoral Scholar within the Accelerator Technology & Applied Physics division under the Berkeley Accelerator Controls & Instrumentation (BACI) Program.

The focus of this role is to contribute to the rapidly evolving field of AI for science and technology, with a focus on developing hardware and FPGA-based control systems for advanced accelerator and laser control applications. Key research areas include superconducting RF cavity resonance control, superconducting magnet quench detection, and real-time feedback systems for high-performance accelerators.

You Will:

• Participate in the design, development, testing, and performance improvement of digital signal processing / FPGA-based Low Level RF (LLRF) control systems for accelerators, including multiple applications such as superconducting RF cavity resonance control, superconducting magnet quench detections, and beam-based undulator controls.
• Contribute to the implementation of LLRF control components, including electronic hardware, FPGA gateware, embedded firmware, and real-time control software.
• Perform hardware integration and system validation, interfacing with FPGAs, RF electronics, cameras, detectors, sensors, and data acquisition systems.
• Design simple APIs and GUIs as the user interface for controlled systems,
• Maintain code repositories, documentation, and software releases in compliance with DOE
• requirements.
• Contribute to publications and community dissemination under DOE open science policies.
• Communicate results through peer-reviewed journal publications, technical reports, and presentations.
• Collaborate effectively in a multidisciplinary research environment.

We are looking for:

• Ph.D. in Electrical Engineering, Applied Physics, Accelerator Physics, or a closely related field within the last 3 years.
• Proven expertise in the full FPGA lifecycle (Xilinx Vivado/Quartus), including gateware development, verification, and debugging.
• Demonstrated R&D experience in FPGA-based real-time controls, specifically Low Level RF (LLRF) or similar accelerator control systems.
• Hands-on experience integrating RF hardware, detectors, sensors, and instrumentation.
• Proven ability to work productively both independently and within multidisciplinary teams.
• Strong written and oral communication skills, with the ability to convey complex technical concepts to diverse audiences.

Desired skills/knowledge:

• Develop and evaluate AI/ML algorithms for accelerator and laser control applications.
• Support model training, analysis, and benchmarking using simulated or experimental data.
• Familiarity with superconducting RF systems, accelerator instrumentation, or laser control systems.