We are seeking a Postdoctoral Research Associate to focus on developing refractive X-ray optics with additive manufacturing. This role involves the advancement of at-wavelength measurement techniques, and will also be instrumental in developing sophisticated data analysis software that incorporates machine learning and artificial intelligence. The successful candidate must be able to work onsite.

Major responsibilities include:

• Collaborating with an industry partner and other scientists at Argonne to design, fabricate, characterize, and optimize additively manufactured X-ray optics.

• Leading research and development in advanced testing and characterization techniques, such as coded-mask-based speckle tracking, grating interferometry, as well as non-X-ray metrologies.

• Developing and demonstrating scientific applications of the refractive X-ray optics.

• Developing and refining modeling of X-ray optics, as well as data analysis and processing software.

• Documenting data meticulously, preparing detailed reports, and presenting results at appropriate conferences and in relevant scientific journals.

Position Requirements

Required Knowledge, Skills, and Experience:

• Knowledge of X-ray physics, interaction of X-rays with matter, beam wavefront and coherence, and the fundamentals of X-ray optics.

• Strong background in data analysis and numerical modeling.

• Skills in designing and conducting experiments, particularly in X-ray science.

• Ability to work both independently and collaboratively within a team environment.

• Exceptional oral and written communication skills, with a track record of effectively presenting research findings.

• Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.

• Understand, value, and promote diversity.

Preferred Knowledge, Skills, and Experience:

• Expertise in coherent diffraction imaging or other coherence-based experimental techniques.

• Understanding fundamentals of X-ray scattering

• Experience in developing and applying machine learning and artificial intelligence techniques within the context of data analysis and/or X-ray optics research.

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