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Postdoctoral Research Associate- Autonomous Scanning Tunneling Microscopy, Quantum Material Reseach

Date: Mar 13, 2023

Location: Oak Ridge, TN, US, 37830

Company: Oak Ridge National Laboratory

Requisition Id 9113 


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 a Postdoctoral Research Associate who will focus on developing and implementing automated experiments with scanning tunneling microscopy (STM), to explore the structural and electronic behavior of quantum materials. This position resides in the Data Nanoanalytics group in the Nanomaterials Characterization section, Center for Nanophase Materials Sciences (CNMS), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL).  


As part of our research team, you will develop and apply autonomous and automated experiments (AE) on state-of-the-art low temperature scanning probe microscopy platforms, with a focus on exploring atomic assembly and behavior of quantum materials. This will involve developing and extending our existing automated experiments platform, driven by python codes that interface with a scanning tunneling microscope (through Labview) to allow complete custom control of the STM hardware for bespoke, smart characterization and materials modification.


Major Duties/Responsibilities: 

  • Develop and implement python-based codes for conducting customized and smart spectroscopies to explore properties of novel quantum materials
  • Perform experiments and analyze data on the fly with connections to edge computing resources
  • Work closely with theory colleagues at the CNMS to improve priors on AE algorithms, to better inform experimental design


Basic Qualifications:

  • A Ph.D. degree in materials science, physics, chemistry, or a related discipline completed within the last 5 years
  • Strong background in scanning tunneling microscopy (STM) research
  • Experience working with ultra-high vacuum (UHV) systems for surface characterization (e.g., XPS, RHEED, LEED, etc.)
  • Data analysis and/or programming skills


Preferred Qualifications:

  • Excellent written and oral communication skills
  • A functional knowledge of machine learning (classical machine learning, and deep learning), and a knowledge of python’s scientific software stack (scipy, numpy, etc.)
  • An excellent record of productive research demonstrated by publications in peer-reviewed journals
  • 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 with the position title and number referenced in the subject line.


Instructions to upload documents to your candidate profile:

  • Login to your account via
  • 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


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

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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