• Job Description

  Req#: 416491

  The X-ray Science (XSD) division at Argonne National Laboratory invites applications for postdoctoral researchers position for a project to develop artificial intelligence (AI) and machine learning (ML) methods to enhance high-energy X-ray diffraction microscopy at the Advanced Photon Source. The extreme volume and velocity of information associated with this non-destructive microstructure mapping technique can benefit from AI/ML at each stage of data flow, from the sensor to the data center. Because such tools can run at high speeds, thanks to advances in AI streaming inference accelerators, it becomes feasible to extract salient information from in-flight data, in real time, and thus both enabling fast feedback and reducing downstream computational burden. The successful candidate will conduct cutting-edge research in data science and deep learning and apply it to scientific problems, particularly in the materials science and engineering fields. The candidate will play a key role in developing physics-aware AI/ML models, developing workflow building blocks and implement high-speed training on data center AI systems (e.g., Cerebras CS-1 ML accelerator and Argonne's Aurora exascale supercomputer), end-to-end model training workflows and explore AI accelerators for simulation applications.

  Position Requirements

  Basic Qualifications:

  • Ph.D. in material sciences and engineering or related field obtained within the last three years.
  • Experience with X-ray science techniques (e.g., tomography, diffraction, etc.).
  • Software development practices and techniques for computational and data-intensive science problems.
  • Comprehensive experience programming in one or more programming languages, such as C, C++, and Python.
  • Ability to provide project leadership.
  • Exceptional communication skills, ability to communicate effectively with internal and external collaborators and ability to work in team environment.
  • Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
  • Understand, value, and promote diversity.

  Preferred Qualifications:

  • Experience with machine learning methods and deep learning frameworks.
  • Experience on applied machine learning (e.g., successful projects that used ML to resolve scientific problems).
  • Experience and skills in interdisciplinary research involving computer and material scientists.
  • Experience with high-performance computing and/or scientific workflow.

  Job Family

  Postdoctoral Family

  Job Profile

  Postdoctoral Appointee

  Worker Type

  Long-Term (Fixed Term)

  Time Type

  Full time

  As an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.

  Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

  All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

• About the company

  Argonne National Laboratory is a science and engineering research national laboratory operated by UChicago Argonne LLC for the United States Department of Energy.

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