[Neutron] ORNL Neutron Sciences Job Posting: Postdoctoral Research Associate - Machine Learning for Neutron Diffraction

Hoffmann, Christina choffmann at ornl.gov
Wed Apr 20 18:26:07 CEST 2022


Email a Friend: Postdoctoral Research Associate - Machine Learning for Neutron Diffraction

Link to Apply<https://jobs.ornl.gov/job-invite/8012/>

Job Title: Postdoctoral Research Associate - Machine Learning for Neutron Diffraction

Requisition Id 8012
Overview:
Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.



We are seeking two Postdoctoral Research Associates who will support the Single Crystal Diffraction and Powder Diffraction Group in the Neutron Scattering Division (NSD), Neutron Science Directorate (NScD) at Oak Ridge National Laboratory (ORNL). The Spallation Neutron Source (SNS) and the High-Flux Isotope Reactor (HFIR) are world-leading facilities and the scientific center of a diverse, international and inclusive neutron scattering community.



As a Postdoctoral Research Associate you will be a member of a team of neutron scattering scientists, computational scientists,­ and engineers at both neutron research facilities as well as enterprise software developers and machine learning experts.
Your research will focus on optimizing and incorporating advanced visualization and neutron data analysis employing machine learning software for scientific studies of magnetism in quantum materials and/or structure of disordered and functional materials.



The project will implement state of the art GPU and parallel computing approaches for visual image processing and multidimensional, interactive visualization of neutron data and analysis. It will involve integrating machine learning software onto existing neutron beamlines for sample alignment and for performing scientific research to study structure and magnetism. Neutron techniques will concentrate on neutron powder and single crystal diffraction, complemented by polarized neutron powder diffraction and inelastic measurements.



This position represents an excellent opportunity to deepen understanding of the properties, magnetism and function of materials and utilize machine learning for visualization and analysis of neutron scattering data in a stimulating multidisciplinary environment at ORNL.



The two positions are split into two focus areas:

  *   Developing visualization and analysis for diffuse scattering data in disordered materials and functional materials.
  *   Developing polarized neutron diffraction methods and other relevant neutron scattering techniques to study magnetism in quantum materials



Major Duties/Responsibilities:

  *   Apply machine learning software to neutron scattering beamlines to optimize measurements and data analysis
  *   Perform neutron scattering experiments and analyze resulting data
  *   Publish scientific papers and present results from this research at national and international meetings as appropriate



Basic Qualifications:

  *   A PhD in physics, chemistry, material science, computational or a related field completed within the last 5 years



Preferred Qualifications:

  *   Background in elastic/ inelastic neutron scattering and analysis or other diffraction methods and analysis
  *   Working knowledge of common or scientific programming languages
  *   Familiarity with machine learning approaches
  *   Experience with either
     *   functional materials and compounds
     *   magnetic materials and measurements
  *   Self-motivated, with the ability to work within a multi-disciplinary team environment on scientifically challenging problems

  *   Excellent written and oral communication skills
  *   Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory
  *   Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs



Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to postdocrecruitment at ornl.gov<mailto:postdocrecruitment at ornl.gov> with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

  *   Login to your account via jobs.ornl.gov<http://jobs.ornl.gov>
  *   View Profile
  *   Under the My Documents section, select Add a Document



Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.



Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the “About” tab at jobs.ornl.gov<http://jobs.ornl.gov>.



This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting at ornl.gov<mailto:ORNLRecruiting at ornl.gov>.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.


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