Assistant Computational Scientist: AI for Bragg Diffraction Imaging

The Advanced Photon Source (APS) (https://www.aps.anl.gov/) at Argonne National Laboratory invites applicants for an assistant computational scientist staff position to develop and apply artificial intelligence (AI) and machine learning (ML) methods for Bragg-based x-ray imaging techniques. This role will focus on advancing the state-of-the-art in Bragg diffraction imaging, including Bragg Coherent Diffraction Imaging (CDI), Bragg ptychography and scanning Bragg Diffraction microscopy.

The successful candidate will:

• Lead a research program focused on creating novel computational methods and AI-driven approaches to solve challenging inverse problems associated with these techniques.

• Be responsible for developing and implementing advanced algorithms and AI/ML models to analyze data from scanning Bragg diffraction, Bragg CDI and Bragg ptychography experiments, with the goal of accelerating data analysis, improving reconstruction quality, and enabling autonomous experiments.

• Work closely with beamline scientists and participate in data-intensive experiments, reporting results in high-impact publications and at international conferences.

This position is part of the Computational Science and AI group (CAI) (https://cai.xray.aps.anl.gov/), a team of cross-disciplinary experts in ML, applied mathematics, high-performance computing, and x-ray science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne, including the upgraded APS and the exascale Aurora supercomputer.

Candidates are encouraged to include a cover letter in addition to a CV.

Position Requirements

• Minimum Experience/Education Requirements: Bachelors and 5+ years’ experience, Masters and 3+ years’ experience, PhD and 0+ years’ experience, or equivalent

• A deep understanding of the physics of x-ray Bragg diffraction imaging and coherent imaging techniques (Bragg CDI, Bragg Ptychography).

• Demonstrated expertise in the associated algorithms and computational methods, such as phase retrieval and other inverse problem solutions.

• Proven experience in developing and applying AI/ML models to scientific problems in the context of imaging or scattering.

• A strong publication record demonstrating innovation in computational methods or AI applied to Bragg imaging or a closely related field.

• Experience with deep learning (DL) libraries such as PyTorch, TensorFlow, or JAX.

• Proficiency in programming, particularly in Python.

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

Preferred Knowledge, Skills, and Experience

• Hands-on experience with data acquisition and analysis from scanning Bragg Diffraction, Bragg CDI or Bragg Ptychography experiments.

• Experience with version control (e.g., Git) and collaborative software development practices.

• Excellent written and oral communication skills, with an ability to interact effectively with a diverse team of scientists.

• Experience with high-performance computing (HPC) environments.

• Familiarity with computational modeling packages relevant to x-ray science or materials modeling.

Job Family

Research Development (RD)

Job Profile

Computational Science 2

Worker Type

Regular

Time Type

Full time

The expected hiring range for this position is $90,063.00 - $143,010.27.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

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