Postdoc - AI/ML and Multiscale Modeling of Materials under Non-Equilibrium Conditions

Requisition Id 16392 

­­Overview:  

We are seeking a highly qualified Postdoctoral Research Associate with experience in developing and/or applying AI/ML methods to model, understand, and discover novel phenomena in materials under non-equilibrium conditions relevant to ion beam-driven processes, field-driven dynamics, and materials synthesis and processing. The position resides in the Nanomaterials Theory Institute (NTI) at the Center for Nanophase Materials Sciences (CNMS) Division, Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL) and will be associated with the Multiscale Dynamics (MD) science theme at the CNMS and related activities.

As part of our research team, you will be working with a highly interdisciplinary team of scientists at the CNMS, and across other divisions at ORNL.

 

Major Duties/Responsibilities: 

• Work closely with other members of NTI and CNMS to provide theory and simulation support, including large-scale molecular dynamics, for materials under non-equilibrium conditions relevant to ion–matter interactions, dynamic ionic motion in solids under applied fields, and synthesis and processing methods such as plasma etching and focused ion beam exposure.
• Develop and apply AI/ML algorithms to enable accelerated discovery of new materials and scientific insights into materials under non-equilibrium and dynamic conditions, leveraging LLM tools when appropriate. This may include the development of machine-learning interatomic potentials (MLIPs), foundational AI models, Bayesian on-the-fly approaches for multi-fidelity simulation and learning, ML methods for beam-induced material modification, synthesis and processing, high-throughput DFT workflows, and interpretable and explainable AI model development.
• Support experimental efforts within the Multiscale Dynamics theme, where the focus is largely on materials relevant to next-generation microelectronics, quantum information systems and energy applications. 
• Present and report research results and publish in peer-reviewed journals in a timely manner
• Ensure compliance with environment, safety, health, and quality program requirements
• Maintain a strong commitment to the implementation and perpetuation of values and ethics.

• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

 

Basic Qualifications:

• PhD in Condensed Matter Physics, Materials Science, Chemistry, Physics, or a closely related science discipline completed within the last five years

 

Preferred Qualifications:

• A strong background in atomistic and/or continuum modeling of materials under non-equilibrium conditions, including beam-matter interactions, high fields, non-equilibrium synthesis, with an emphasis on solid-state materials (2D materials, ultra-wide bandgap semiconductors, ferroelectrics, twisted materials etc.)
• Hands-on expertise in developing and applying machine-learned interatomic potentials (MLIPs) to problems in solid-state materials
• A demonstrated record of applying advanced AI/ML methods for scientific discovery
• Expertise in using high-performance computing (HPC) platforms for enabling advanced scientific discovery 
• A record of productive and creative research proven by publications in peer-reviewed journals and/or conference presentations
• Demonstrated ability to initiate and advance research directions independently
• Demonstrated ability to contribute creatively and effectively within a collaborative team environment
• Demonstrated ability to manage multiple priorities, adapt to evolving research needs, and work effectively across multiple projects in a collaborative research environment
• 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.

 

Special Requireme