Postdoctoral Research Associate - MSD - Van De Waals Materials

Argonne National Laboratory

Lemont, USA

Job posting number: #7175655 (Ref:416464)

Posted: September 2, 2023

Application Deadline: Open Until Filled

Job Description

Postdoctoral Appointee positions are available within the Materials Science Division (MSD) at Argonne National Laboratory. A successful candidate will work with a group of scientists in MSD to explore the evolution of van der Waals materials under external electric and optical stimuli using coherent and / or ultrafast X-ray photons. The candidate will be able to take full advantage of the highly coherent X-rays from the upgraded Advanced Photon Source (APS), the THz laser within MSD and the aberration-corrected Lorentz transmission electron microscope within MSD, as well as X-ray Free Electron Laser facilities around the world.

In this role the successful candidate will:

  • Perform pioneering experiments to reveal the driven spatiotemporal evolution of electronic order and domains in van der Waals materials;

  • Develop novel experimental methods and simulations for understanding and interpreting the experimental results;

  • Publish results in refereed journals and make oral presentations at meetings, conferences, symposia, and seminars.

Position Requirements

We expect the successful candidate to have:

  • A Ph.D. in physics, applied physics, materials science or a related field.

  • Knowledge in one of the following areas: van der Waals materials, ferroelectrics, correlated oxides or energy conversion and storage materials.  

  • Experience in one of the following: X-ray diffraction, crystallography, Lorentz transmission electron microscopy, ultrafast studies of materials

  • Experience with advanced data analysis implemented in languages such as Python or MATLAB.

  • Strong written and oral communication skills.

  • Ability to collaborate and work with a team in an interdisciplinary environment.

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

Having one of following experiences would be highly desirable:

  • Fabrication and characterization of quantum materials and heterostructures

  • Experience with machine learning/deep learning methods

To be eligible, candidates must have completed their Ph.D. within the last three years, or be expecting their Ph.D. within the next 12 months. 

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.  

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Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.


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