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Theory Postdoctoral Research Associate in Computational Materials Theory and Discovery

Los Alamos National Laboratory
Los Alamos, NM Full Time
POSTED ON 9/17/2026
AVAILABLE BEFORE 10/24/2026
What You Will Do

The Quantum and Condensed Matter Physics Group in the Theoretical Division of Los Alamos National Laboratory (LANL) has an immediate opening of postdoctoral position in the area of computational materials physics. The postdoc will focus on applying first-principles density functional theory (DFT) and high-throughput approaches in combination with machine learning techniques for discovering and the inverse design of novel 2D f-electron materials with non-trivial topological properties. The work will be a combination of developing computational workflows and applying existing DFT codes. Successful applicants will join a highly collaborative project aimed at unraveling both the fundamental properties of these systems and establishing a new route to quantum information and laying the foundation for future quantum information devices and be an integral part of a dynamic team of condensed matter theory and experiment scientists at Los Alamos National Laboratory and University of California, Irvine.

What You Need

Minimum Job Requirements:

A successful candidate must demonstrate strong skills in computational materials theory with an excellent scientific record of publications. Expertise in first-principles density functional theory simulations (i.e., working experience with standard DFT methods, such as VASP, Quantum Espresso, or Wien2k) and experience programming in either Python, C , or Fortran is required while knowledge of machine learning is highly desired, but not necessary. The ability to work creatively as a part of a diverse team and independently is important. Strong written and oral communication skills are essential.

Education: Candidates must have a Ph.D. in Physics, Chemistry, or Materials Science (completed within the last 5 years).

Desired Qualifications:

  • Experience working in Linux computing environments, especially in the context of high-performance computing.
  • Experience or knowledge of basic machine learning methods.

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.

Further inquiries can be addressed to Dr. Christopher Lane (email: laneca@lanl.gov) or Dr. Ying-Wai Li (email: yingwaili@lanl.gov).

Please apply for the position online, and also send a resume, publication list, research interest, a brief statement of future plans and the names of three references to Dr. Christopher Lane (email: laneca@lanl.gov). The position has an initial appointment of two years. Additional information on salary ranges and other benefits can be found online at http://www.lanl.gov/postdocs/.

Candidates may be considered for a Director's Fellowship and outstanding candidates may be considered for the prestigious Darleane Hoffman, Richard P. Feynman, or J. Robert Oppenheimer Fellowships. For general information refer to the Postdoctoral Program webpage.

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.

Instructions on How to Activate/Create a LANL Jobs Account:

Follow the instructions below if you have ever had an employee Z number, been a contractor, or received Los Alamos Lab insurance coverage to activate your account:

  • Select the Click Here button if you have been employed with the Lab or received insurance coverage.
  • Please enter only your first and last name and current email address (an email with your validation code will be sent to you) to activate the account currently in our system.
  • Enter your validation code as described in the email you receive and complete the 3-page registration form. Your account is now active, and you can apply for jobs or save to your basket. Important: Enter the validation code within 15 days to activate your account or your account will be deactivated.

Follow the instructions below if you if you have never been employed with the Lab or received insurance coverage to create an account:

  • Select the Register button if you have never been employed with the Lab or received insurance coverage to Create an Account.
  • From here, you will establish an account with username and password.

How to Apply: Login to Your Account to Complete the Application Process

  • Click the Vacancy Name number (in blue) to view any job's details.
  • Click Apply or Add to Basket to apply later. Tip: To apply for a job or save your basket, you must have a LANL jobs account.

If you experience any technical issues, please email applyhelp@lanl.gov for assistance.

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