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Postdoctoral Research Associate - Autonomous Scanning Probe Microscopy

Date: Jun 2, 2022

Location: Oak Ridge, TN, US, 37830

Company: Oak Ridge National Laboratory

Requisition Id 8171 


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 support the Data Nonoanalytics Group in the Theory and Computation section, Center for Nanophase Materials Science Division (CNMS), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). The Postdoc will focus on developing and implementing automated experiments with scanning probe microscopy (SPM), to explore the structural and electronic behavior of quantum materials. 


As part of our research team, you will develop and apply autonomous and automated experiments (AE) on scanning probe microscopy platforms, with a focus on exploring local 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 PhD in materials science, physics, chemistry, or a related field completed within the last 5 years


Preferred Qualifications:

  • At least one year of knowledge of the scientific software stack in python (numpy, scipy, scikit-learn)
  • Knowledge of machine learning such as clustering, dimensionality reduction, and basic image processing
  • A functional knowledge of machine learning, with an emphasis on Bayesian statistics or reinforcement learning
  • Strong background in low temperature UHV scanning tunneling microscopy (STM) research
  • An excellent record of productive research demonstrated by publications in peer-reviewed journals
  • 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 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.

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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.

Nearest Major Market: Knoxville