Please apply at https://jobs.ornl.gov/job-invite/9587/

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 support the Materials Theory Group in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL) who will apply or/and develop many-body ab-initio methods and high throughout methods to explore the properties of correlated or/and topological materials. This is a synergistic effort involving an Advance Materials Theory field work proposal (FWP) and the Center for Predictive Simulation of Functional Materials, a DOE-funded Computational Materials Sciences (CMS) Center (https://cpsfm.ornl.gov).  

The goals of our synergistic efforts are i) to understand challenging and intriguing materials with the most advanced methods, ii) develop and deploy advanced, systematically improvable quantum Monte techniques.  Our efforts aim to demonstrate and develop a new capacity of QMC techniques in combination with density functional theory to conclusively predict, and hence ultimately design, the properties of correlated, topological, and quantum materials where understanding competing effects is of great importance.  Computational research will be engaged closely with experimental studies.  The available funding for this position can flexibly accommodate candidates with preferences on computational implementations or applications. Successful applicants will have many opportunities for collaboration with computational theorists and experimentalists across 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 correlated materials and experience with algorithm and code development. The ideal resume should show creative work not limited to a repetitive application of licensed codes.

Major Duties/Responsibilities: 

• Learn/deploy many-body methods, such as diffusion and auxiliary field Monte Carlo, GW DMFT etc.
• Perform QMC and other calculations on high performance computers with the QMCPACK code to investigate the many body electronic properties of functional and topological materials
• Perform initial density functional theory studies with codes such as Quantum Espresso
• Plan and effectively execute computational research projects and perform detailed analysis of data in the context of quantum mechanics 
• Present and report research results at group meetings and international conferences
• Publish scientific results in peer-reviewed journals in a timely manner
• Ensure compliance with environment, safety, health, and quality program requirements
• Maintain strong dedication to the implementation and perpetuation of values and ethics

Basic Qualifications:

• A PhD in Materials Science, Computer Science, or a related field completed within the last 5 years
• Demonstrated experience in first-principles calculations in density functional theory, and beyond DFT methods such quantum chemistry, dynamical mean field theory, GW, or 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
• Programming experience with Python
• Experience working in Linux computing environments, especially in the context of high-performance computers

• 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 apply at https://jobs.ornl.gov/job-invite/9587/