Requisition Id 10789 

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 a Postdoctoral Research Associate who will focus on applying and/or developing many-body quantum Monte Carlo (QMC), high-throughput, or machine learning methods to explore the properties of correlated and/or topological materials. This is a joint synergistic effort involving an Advance Materials Theory Field Work Proposal and the Center for Predictive Simulation of Functional Materials, a DOE-funded Computational Materials Sciences (CMS) Center (https://cpsfm.ornl.gov). This position resides in the Materials Theory Group in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL).

As part of our research team, we will be able to flexibly accommodate your research preferences either towards immediate scientific applications or towards new methods and computational implementations. You could be involved in one or more aspects of applying modern electronic structure methods to correlated, topological, and quantum materials. Our method development includes Quantum Monte Carlo (QMC) techniques, high-throughput density functional theory (DFT), and machine learning. Your research will engage closely with experimental studies. Successful applicants will have immediate and potential future opportunities for collaboration with computational theorists and experimentalists at multiple national laboratories, including Oak Ridge, Argonne, Sandia, and Lawrence Livermore national laboratories. 

The ideal candidate will have detailed knowledge of quantum mechanics, statistical methods, and experience in the application of computational electronic structure methods to novel materials and experience with algorithm and code development. An ideal resume would show creative work not limited to a repetitive application of established methods and licensed codes.

Major Duties/Responsibilities: 

• Perform electronic structure research using modern electronic structure methods for novel correlated topological and quantum materials
• Explore use of high-throughput and machine learning methods
• Present and report research results at group meetings and international conferences
• Publish scientific results in peer-reviewed journals in a timely manner
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote diversity, equity, inclusion, and accessibility by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• A PhD in Physics, Chemistry, Materials Science, Computer Science, or a related field completed within the last 5 years
• Demonstrated experience in first-principles calculations using one or more modern electronic structure techniques, including high-throughput DFT, quantum chemistry, dynamical mean field theory, GW, or ab initio quantum Monte Carlo

Preferred Qualifications:

• An excellent record of productive and creative research demonstrated by publications in peer-reviewed journals
• Experience developing electronic structure methods, and contributing to or releasing open-source codes in Python or C++

• 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@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
• 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.

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@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.