Postdoctoral Research Associate in the Physics and Chemistry of Materials Group

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 85,000 - 100,000; Full time

Benefits offered by this job

Medical insurance

Dental and vision insurance

Life and disability insurance

Parental leave

401(k) matching

Tuition assistance

Flexible schedules and PTO

Relocation packages

Job summary

Los Alamos National Laboratory seeks postdoctoral researchers to advance machine learning interatomic potentials for catalysis, electrochemistry, polymers, and chemical reactivity. You will train and validate models using LANL data and public datasets, then deploy them on HPC clusters like El-Capitan to support mission-critical predictions.

The role includes collaboration with theorists and experimentalists, proposal writing, and presenting modeling results at conferences.

Qualifications

• A PhD in Computer Science, Applied Mathematics, Physics, Chemistry, Materials Science, or related fields, completed within the last five years or soon to be completed.
• Strong programming skills, notably in Python and deep learning libraries (JAX/PyTorch/TensorFlow).
• Experience with machine learning models and conducting original scientific research with publications.

Responsibilities

• Develop and apply ML interatomic potentials (MLIPs) for predicting chemical and material properties.
• Deploy models on HPC clusters (e.g., El-Capitan) to impact LANL mission needs.
• Contribute to proposal writing, program development, manuscript preparation, and conference presentations.

Education

PhD in Computer Science, Applied Mathematics, Physics, Chemistry, Materials Science, or related fields

Tools

Python

JAX

PyTorch

TensorFlow

CUDA

Job description

What You Will Do

The Physics and Chemistry of Materials group (T-1) at Los Alamos National Laboratory is seeking qualified applicants for postdoctoral positions. The candidate will be expected to perform outstanding research at the intersection of machine learning, materials science, and chemistry on world leading HPC systems. The members of the T-1 group, who would sponsor the postdoctoral associate, are experts in theory and simulation of materials as well as the application of machine learning techniques to a wide range of problems.

Within the T-1 group, the selected applicant will focus on the development and application of machine learning interatomic potentials (MLIPs) for the prediction of chemical and material properties. Specifically, this research will focus on areas such as catalysis, electrochemistry, soft matter systems such as polymers, and chemical reactivity. Of particular interest is the development of optimal methods for maximizing the improvement of MLIPs from limited, high accuracy data sources, such as those produced by experimental methods or from simulations preformed on a quantum computer. The applicant will work with a variety of database structures and public and LANL owned data to train and validate these models. Once constructed, the candidate will deploy these models on HPC clusters such as El-Capitan to directly impact LANL mission needs. The applicant will also aid in proposal writing and program development to pursue new solutions to current challenges. Finally, the applicant will lead the preparation of manuscripts and develop conference presentations based on modeling successes demonstrated in the mission space.

What You Need

Minimum Job Requirements

• Strong programming skills, notably in Python and deep learning library JAX/Pytorch/Tensorflow,


• Experience with machine learning models.


• Demonstrated experience in conducting original scientific research through peer reviewed publication record.


• Ability to operate autonomously with minimal oversight.


• Excellent communication skills (both oral and written).


• A PhD in Computer Science, Applied mathematics, Physics, Chemistry, Materials Science, or related fields, completed within the last five years or soon to be completed.

Desired Qualifications

• Experience with High Performance Computing (HPC) or Graphics Processing Unit (GPU) computing.


• Strong programming skills in C/C++ and/or GPU-centric languages such as CUDA.


• Experience collaborating with experimental researchers in chemistry and materials science.


• A collaborative spirit with the aptitude to work synergistically within a multi-disciplinary team.


• U.S. citizen with willingness to apply for a clearance.

Work Environment

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.

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.

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 [e-mail] or call (505)-664-6947.