Postdoctoral Appointee - ML/AI for X-ray Scattering to Enhance Structural Resolution

The Chemical and Materials Science group in the X-ray Science Division is seeking a highly motivated Postdoctoral Appointee. X-ray scattering is a key technique at the Advanced Photon Source (APS), widely utilized for characterizing biomacromolecules, polymers and other nano-scale structures.

The successful candidate will join an interdisciplinary team and leverage machine learning or artificial intelligence (ML/AL) algorithms and other computational methods to enhance the structural resolution of current X-ray scattering techniques. This position offers the opportunity to work at state-of-the-art X-ray scattering beamlines at APS and apply the developed methods for detailed structural characterization.    

Position Requirements

• This level of knowledge is typically achieved through a formal education in Physics, Biophysics, Physical Chemistry, or a related field at the PhD level with zero to five years of employment experience.

• Experience with scientific programing. 

• Excellent oral and written communication skills.

• Ability to collaborate effectively in an interdisciplinary research team setting.

• Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.

• Ability to understand, value, and promote diversity, equity, inclusion, and accessibility.

Preferred Knowledge, Skills and Experience

• Experience with biomolecular Molecular Dynamics Simulations.

• Familiarity with Machine Learning / Artificial Intelligence.

• Familiarity with standard data science and machine learning python libraries.

• Hands-on experience with X-ray scattering techniques.

Job Family

Postdoctoral Family

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

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