Postdoctoral Appointee - Machine Learning for Particle Accelerators

The Accelerator Operations and Physics (AOP) Group of the Accelerator Systems Division (ASD), Advanced Photon Source (APS) is hiring a postdoc researcher for a multi-year appointment. The postdoc researcher will work to develop advanced ML methods for accelerator tuning and control, as well as beam diagnostics, with applications to APS injector, and APSU storage ring commissioning and operation. Experimental work on the existing APS injector accelerator complex and the new APS Upgrade storage ring will be done to test the methods and to assess their usefulness for accelerator operation. The research work is supported by an on-going DOE-funded ML R&D project.

Controls of modern complex accelerators at large scale scientific user facilities have become increasingly more challenging as new machines push technology limits in the quest for higher performance. Using beam-based diagnostics to identify machine errors that affect the performance and tuning available control parameters will be critical in realizing the design performance of future machines, while applying advanced control methods to accelerator optimization and control during operation will be necessary in maintaining high performance. Machine learning techniques have found use in accelerator tuning and control in recent years. In this ML R&D project, we will apply existing methods to important tuning and control problems on injectors and storage rings, explore and develop more efficient and more robust methods to address the challenges. Studies will also be conducted on using ML methods to analyze operation history data in order to extract information to inform accelerator maintenance schedule and to detect and predict component failures. We will collaborate with ML researchers at SLAC and Brookhaven National Laboratories.

Position Requirements

Qualifications:

• PhD degree within the last three years in accelerator physics or related fields
• Recent PhD graduates in other branches of physical sciences, or in math, computer science, and electric engineering who have an interest in accelerator physics will also be considered
• Strong programming skills
• Proficiency in the Python programming language
• Working knowledge of UNIX or Linux

Desired Skills:

• Experience with machine learning and accelerator operation
• Experience working with complex algorithms
• Experience with accelerator modeling and simulation codes, such as Elegant
• Experience using computing clusters for simulation and data analysis
• Experience with SDDS, Tcl/Tk, and scripting in Linux environment

Job Family

Postdoctoral Family

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

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