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Postdoc on Modeling+ML for Experimental Characte ... (No replies)

mkychan
2 years ago
mkychan 2 years ago

The Center for Nanoscale Materials (https://www.anl.gov/cnm) at Argonne National Laboratory (near Chicago, US) has immediate postdoctoral openings in the use of computational modeling and machine learning to interpret experimental x-ray, electron, and scanning probe characterization data. The postdoctoral researchers will work within the group of Dr Maria Chan (https://www.anl.gov/profile/maria-k-chan) on developing and applying algorithms and software to (1) use machine learning, specifically deep learning, to accelerate the interpretation of electron and scanning probe microscopy data, and (2) perform first principles and atomistic modeling and machine-learning assisted design of materials. The postdoctoral researchers will be collaborating extensively with researchers at Argonne, other national laboratories, as well as universities.

Applicants should have expertise in some of the following:
• Density functional theory/molecular dynamics modeling of materials, e.g. high throughput calculations, structure prediction, classical and ab initio MD simulations
• Simulation of experimental characterization signals, e.g. x-ray spectroscopy, electron microscopy, scanning tunneling microscopy, and neutron scattering.
• Use of machine learning approaches
• Development and implementation of algorithms and software for materials modeling
• High-performance and parallel computing
Excellent communication and analytical skills are required. Ability to work independently and in an interdisciplinary collaborative environment, in close collaboration with experimentalists, is expected. Software programming experience is necessary. A PhD in computational physics, chemistry, materials science, chemical engineering, or a related field is required.

Interested candidates should email [email protected] with the following information:

  1. A detailed curriculum vitae (lastname_firstinitial_CV.pdf) including a list of publications and the names and email addresses of three professional references.
  2. A cover letter (lastname_firstinitial_CL.pdf), including
    a) description of previous materials modeling experience (techniques, materials, key contributions);
    b) description of machine learning experience;
    c) description of software development experience;
    d) expected start date
    e) USA citizenship/visa/work eligibility status (if known).
  3. One representative publication (lastname_firstinitial_paper.pdf) that best showcases your work.

Questions should be directed to [email protected]. Postdoctoral appointments are on a one-year basis, with a maximum term of three years, subject to performance evaluation. Argonne National Laboratory offers excellent compensation and benefit packages, and postdoctoral researchers receive extensive career development guidance. Dr Maria Chan received an Outstanding Postdoctoral Supervisor award from Argonne and former postdoctoral associates have acquired desirable faculty and industry positions. Argonne is a U.S. Department of Energy laboratory managed by UChicago Argonne, LLC. Argonne is an equal opportunity employer, and we value diversity in our workforce.




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Ab initio (from electronic structure) calculation of complex processes in materials