NIST | Postdoc in AI/Quantum Materials| Gaithersburg, Maryland, USA| ONSITE
I am advertising two postdoctoral opportunities available through the National Research Council (NRC) program at the NIST Center for Neutron Research (NCNR).  The program is described at <a href=".  The neutron scattering group at the NCNR is strongly collaborative and the successful candidate will have a great deal of independence and intellectual freedom as well as a generous stipend ($72,000).  Online applications for the NRC are open December 1st and end February 1st. US Citizenship required. Interested applicants should contact REDACTED_EMAIL. There are two projects that are of primary interest:
1) Applications of machine learning to neutron scattering with an emphasis on experimental 
optimization and reinforcement learning.  You can think of this as modern experimental design.  Where do we measure to obtain the most information?  Other applications could include Bayesian model selection approaches to diffraction and inelastic data.  For example, can we automatically detect the space group from powder diffraction data?  Where do we measure to distinguish between two magnetic Hamiltonians?   The ideal applicant would have a background in science and interest/experience with ML/AI.  For example, suppose you are in condensed matter (experiment or theory) and are thinking of getting into ML.  I’m also open to those with more of a CS/ML background who want to apply their skills to a problem in physics.
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Minimum Skills
Programming skills: Experience with using Python, IDL, or Matlab to plot/analyze data
Either:  Experience with science at a PhD level or experience with ML/AI
Ideal Skills
Programming skills: Experience with tensorflow, pytorch, scikit-learn
Science: Expertise in a neutron scattering technique used to study hard condensed matter systems.  This could be time-of-flight, triple-axis-spectometry, or magnetic diffraction applied.  Expertise with synchrotron x-ray diffraction techniques would be just as welcome.
2) Study of Quantum Materials, Topological Insulators, Skyrmions, Spin Liquids, or Multiferroics using neutron scattering as a probe.  Recently, we have collaborated with a number of groups to study materials ranging from magnetic topological insulators to multiferroic skyrmions.  In addition to performing neutron scattering opportunities, the successful applicant will have the opportunity to grow high quality thin films or single crystals via existing collaborations in the area..
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Minimum Skills
Programming skills: Experience with using Python, IDL, or Matlab to plot/analyze data
Scientific experience:  Experience with hard condensed matter physics.   Even if you have not done neutron scattering before it’s fine as long as you have a good knowledge of hard condensed matter (for example, you might have done some synthesis/growth and susceptibility measurements).
Ideal Skills
Scientific experience: Expertise in a neutron scattering technique used to study hard condensed matter systems.  This could be time-of-flight, triple-axis-spectometry, or magnetic diffraction applied.  Expertise with synchrotron x-ray diffraction techniques would be just as welcome.