Artificial Intelligence for Materials Postdoctoral Research Associate Job at Los Alamos National Laboratory, Los Alamos, NM

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  • Los Alamos National Laboratory
  • Los Alamos, NM

Job Description

What You Will Do

The Physics and Chemistry of Materials group (T-1) at Los Alamos National Laboratory seeks a highly motivated post-doctoral candidate, in the areas of Artificial Intelligence (AI) and materials science, with an emphasis on materials under extreme conditions and generative AI (GenAI). Successful applicants will work in Group T-1 (Physics and Chemistry of Materials) of the Theoretical Division and collaborate with a larger group of scientists and postdocs from MPA-CINT and XCP organizations.

This postdoctoral position is part of a larger project that is focused on developing GenAI models of process-structure-property relationships for materials discovery. 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:
  • Excellent understanding of advanced Artificial Intelligence architectures and algorithms, and their application for materials science
  • Experience training Artificial Intelligence models with PyTorch, TensorFlow
  • Atomistic simulations of materials (Mechanics of Materials)
  • Multiscale modeling of materials
  • Strong programming skills in Python
  • 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, Computer Science, Computational Physics, Engineering, or related fields, completed within the last five years or soon to be completed.

Desired Qualifications:
  • Experience in training large Artificial Intelligence models on GPU-accelerated super computers, with large workloads, and familiarity with PyTorch Lightning, Hugging Face, LangChain etc.
  • 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.
Location

This position will be physically located in Los Alamos, New Mexico.

Salary: Competitive salaries are based on the date the PhD degree requirements were completed or the degree was awarded. Starting salary for a new graduate is currently $94,500. For more information go to Postdoc Program website at

Note to Applicants:

For more information on Postdoc program at LANL, please refer to

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

Contact:

Dr. Avanish Mishra ([email protected])

Dr. Nithin Mathew ( [email protected] )

Dr. Saryu Fensin ([email protected])

Fulltime or part time options available.
Where You Will Work

Located in northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns.

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.

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.

Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regard to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation or preference, 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 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 [email protected] or call 1-505-665-4444 option 1.

How to Apply: 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. 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: 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 [email protected] for assistance.

Job Tags

Holiday work, Full time, Part time, For contractors, Relocation, Flexible hours,

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