Distinguished Postdoctoral Research Associate - Science Engagement

About the role

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 Science Engagement Section in the National Center for Computational Sciences (NCCS), Computing and Computational Sciences Directorate (CCSD) at ORNL to perform leading-edge computational materials research and development. The scientific focus of this role is the study of the chemical and physical properties of molten salt liquids relevant to fission and fusion reactors. The production and recovery of tritium fuel are major challenges for successfully generating fusion energy. This research will focus on the chemical speciation and transport of tritium in the molten salt blankets using ab initio quantum simulations, machine learning potentials, and statistical mechanical theory. Collaborations with internal and external fusion efforts will be strongly encouraged. The successful candidate will be mentored and teamed with staff in the National Center for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically targeted at the key DOE Office of Science missions.

Responsibilities

• Work closely with ORNL researchers in using the resources of the OLCF effectively and efficiently
• Develop and port scalable materials science applications and algorithms for OLCF supercomputers
• Develop and apply advanced, compute-intensive materials simulation methodologies to study the fundamental properties of molten salt materials to meet scientific objectives
• Debug and profile applications for high performance
• Conduct research and report results in journal publications, conference papers and technical manuals

Requirements

• A PhD in Computational Chemistry, Physics, Chemical Engineering, Materials Science and Engineering, or a related field completed within the last 5 years
• Experience in theoretical and computational quantum simulations of materials or chemical physics methods, in particular ab initio and AI-driven simulation methods
• Experience in statistical mechanical theory to analyze the simulation results
• Basic understanding of parallel application development techniques (parallel programming models, algorithms, and software)
• Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete