Physics Informed Machine Learning Jobs in Tennessee

Requisition Id 15880
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 an outstanding Postdoctoral Research Associate with a strong background in condensed-matter physics and materials science and expertise in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte carlo), as well as experience in developing and/or applying advanced AI/ML methods to accelerate materials discovery. The project will involve integrating such theory-informed AI-models for creating integrated autonomous experimental synthesis and characterization cross-facility agentic-AI platforms that allow real-time guidance and control of these multi-modal experiments for targeted discovery of novel quantum and/or microelectronic materials, enabling Labs-of-the-Future (LoTF) for breakthrough science. The position resides in the Nanomaterials Theory Institute (NTI) within the Theory and Computation Section (TACS) at the Center for Nanophase Materials Sciences (CNMS) Division, Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL) and will also have opportunities to collaborate with the Multiscale Dynamics and Heterogeneities in Quantum Materials themes at the CNMS and US DOE's Genesis projects. The candidate is expected to work closely with Soumendu Bagchi and P. Ganesh.
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 members of NTI and CNMS to develop HPC workflows that can perform multi-fidelity simulations to predict and interpret a wide range of structural and electronic characterization techniques
• Develop physics-informed AI/ML surrogate models for inverse design of new materials and processes, incorporating simulated and experimental multi-modal datasets.
• Develop AI/ML approaches to bridge length- and time-scales in simulations.

• Design, develop, and validate physics-informed AI/ML models with features from electronic structure, spectroscopy to control materials growth and emerging functionalities.
• Develop and train agentic AI tools that can control simulation and/or experiments.
• 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.

Basic Qualifications:

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

Preferred Qualifications:

• A demonstrated record of developing advanced physics-informed AI models for scientific discovery
• Hands-on expertise developing and applying machine learning for materials and/or process discovery, particularly quantum and/or microelectronic materials
• Expertise in using or developing agentic tools for automation of scientific discovery
• Expertise in using high-performance computing (HPC) platforms for delivering breakthrough scientific results
• A record of productive and creative research proven by publications in peer-reviewed journals and/or conference presentations
• The abilities to be a self-starter, to work independently, and to participate creatively in a collaborative team effort
• Proven ability to function well in a dynamic research environment, set priorities, multi- task and adapt to ever changing needs

Security, Credentialing, and Eligibility Requirements
For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.
To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
Postdoctoral Research Associates:
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 up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.
Recommendation Letters:
Please submit three letters of reference when applying for 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

About ORNL:
As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation's most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.
ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.
Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.
If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@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.
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.