Research Associate in machine learning and x-ray science at SLAC National Accelerator Laboratory, Menlo Park, California, USA

A research associate position is available at SLAC National Accelerator Laboratory, as a part of a collaboration between the Linac Coherent Light Source and Accelerator Directorates, and Machine Learning Initiative. The position focuses on developing new machine learning approaches to enable automatic alignment of complex instruments for ultrafast quantum matter research at the 1-MHz Free-Electron-Laser LCLS-II. 

 

Please find a brief job description below and more details here. 

 

Position overview:

SLAC National Accelerator Laboratory is seeking Research Associates with a proven track record of scientific achievement applying machine learning (ML) techniques and a background in material science, ultrafast x-ray sciences.

 

In this position, you will be supporting a research effort managed by the Linac Coherent Light Source (LCLS) and Laboratory Directed Research and Development (LDRD) program. You will focus on developing a model to enable end-to-end alignment of electron probes that are integrated with 1-MHz LCLS-II. This will expand the horizon of complex photoelectron spectrometers and capabilities. Multi-lens configurable electron optics coupled with a state-of-the-art free electron laser will allow the exploration of exotic quantum materials, nanomaterials, and complex gas phase systems. To reduce the time to alignment in this system, an end-to-end machine learning-directed model will be developed to automate the alignment of the electron optics. Efforts here focus on a specific use case at LCLS-II. The overall aim is to build digital twins of the spectrometers. This will consist of a high-fidelity multi-physics model capable of describing the micro and macro features of the electron imaging lens. Mirroring the state of and behavior of the physical system is a key goal of this project. The research associate will also participate and expected to lead experiments at facilities.  

 

Note: The Research Associate role is a fixed term staff position. Appointment duration is 12 months, with the possibility of extension. Assignment duration is contingent upon project needs and funding.

 

Preview of applications begins immediately. Applications are accepted until the position is filled. Interested candidates should submit a cover letter, CV, and three references to Quynh Nguyen (qlnguyen@slac.stanford.edu