Artificial Intelligence for Materials Postdoctoral Research Associate
- Req. Number: IRC142755
- Organization : MPA-CINT/Center For Integrated Nanotechnologies
- City, State: Los Alamos, New Mexico
The Materials Physics and Application Division -Center for Integrated Nanotechnologies (MPA-CINT) and Theoretical Division-Physics and Chemistry of Materials (T-1) at Los Alamos National Laboratory seeks a highly motivated post-doctoral candidate, in the areas of machine learning and AI for materials science, with an emphasis on learning from materials datasets to establish structure-property relationship. Successful applicants will work in Group CINT of the Materials Physics and Application Division and collaborate with a larger group of scientists and postdocs from across organizations.
This postdoctoral position is part of a larger project that is focused on ML/AI model for regression, classification, and uncertainty-aware prediction to connect microstructure/defect descriptors (from simulations and/or imaging-derived features) to materials properties and performance. The successful applicant will be expected to integrate with the project team broadly and coordinate with experimentalists. The results are expected to be published in peer-reviewed journals and presented at prominent conferences. We provide unique opportunities for cross disciplinary collaborations, scientific workshop organization, and conference attendance. Outstanding applicants may be nominated for prestigious LANL-funded fellowships, enabling the pursuit of independent research.
What You Need
Minimum Job Requirements:
Demonstrated expertise in one or more of the following:
- Machine learning for materials data, including regression and classification on materials and microstructure datasets.
- Materials modeling experience relevant to microstructure and mechanics (e.g., MD/DFT, phase-field, crystal plasticity, microstructure-property relationships).
- Uncertainty quantification (UQ) and model reliability, including approaches such as calibrated probabilistic prediction, Bayesian/ensemble methods.
- Development and use of atomic-scale descriptors for learning from atomistic datasets (SFD, ACE, MTP, SNAP), including feature construction, and integration into ML workflows.
- Strong programming skills in Python (e.g., NumPy/SciPy, pandas,) and ML frameworks such as scikit-learn, PyTorch, JAX, and TensorFlow.
- Demonstrated experience in conducting original scientific research through peer reviewed publication record.
- Excellent communication skills (both oral and written).
Education/Experience: A STEM PhD in areas such as Materials Science, Computational Physics, Engineering, or related fields, completed within the last five years or soon to be completed.
Desired Qualifications:
- Solid Background in materials science and engineering.
- Experience training ML/AI models at scale on GPU-accelerated HPC systems, including managing large datasets/workloads and performance-aware workflows.
- Ability to adapt to new requirements for projects and be flexible enough to learn new areas of research as needed.
- Ability to work effectively as a part of a team in a multi-disciplinary environment and interact with people with a variety of expertise.
Note to Applicants:
Due to federal restrictions contained in the current National Defense Authorization Act, citizens of the People's Republic of China-including the special administrative regions of Hong Kong and Macau-as well as citizens of the Islamic Republic of Iran, the Democratic People's Republic of Korea (North Korea), and the Russian Federation, who are not Lawful Permanent Residents ("green card" holders) are prohibited from accessing facilities that support the mission, functions, and operations of national security laboratories and nuclear weapons production facilities, which includes Los Alamos National Laboratory.
For more information on Postdoc program at LANL, please refer to https://www.lanl.gov/careers/career-options/postdoctoral-research/postdoc-program/index.php
Candidates may be considered for a Director's Fellowship and outstanding candidates may be considered for the prestigious Marie Curie, Richard P. Feynman, J. Robert Oppenheimer, or Frederick Reines Fellowships. For general program information, refer to the Postdoc Program web page https://www.lanl.gov/careers/career-options/postdoctoral-research/postdoc-program/index.php
Contact:
Dr. Avanish Mishra (avanish@lanl.gov)
Dr. Saryu Fensin (saryuj@lanl.gov)
Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.
Where You Will Work
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:
§ PPO or High Deductible medical insurance with the same large nationwide network
§ Dental and vision insurance
§ Free basic life and disability insurance
§ Paid childbirth and parental leave
§ Award-winning 401(k) (6% matching plus 3.5% annually)
§ Learning opportunities and tuition assistance
§ Flexible schedules and time off (PTO and holidays)
§ Onsite gyms and wellness programs
§ Extensive relocation packages (outside a 50 mile radius)
Additional Details
Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.
No Clearance: Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks.
New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.
Internal Applicants: Regular appointment employees who have served the required period of continuous service in their current position are eligible to apply for posted jobs throughout the Laboratory. If an employee has not served the required period of continuous service, they may only apply for Laboratory jobs with the documented approval of their Division Leader. Please refer to Policy Policy P701 for applicant eligibility requirements.
Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to applyhelp@lanl.gov or call (505)-664-6947.