Machine Learning for Science Postdoctoral Research Associate

What You Will Do

The Earth and Environmental Sciences (EES) Division at Los Alamos National Laboratory (LANL) has an opening for a postdoctoral research associate in artificial intelligence for scientific discovery. We are searching for a highly motivated candidate with expertise in machine learning and a passion for pushing the frontiers of science. The successful candidate will work on a multidisciplinary team to train and deploy large models for scientific applications.

In this role, you will have the unique opportunity to work on cutting-edge machine learning models that predict material properties. One particularly exciting part of the project is the development of a foundation model designed to understand how complex materials react under different boundary conditions. This model leverages billions of parameters and integrates insights from multiple physics simulators. Together with the team you'll contribute to creating a tool that could revolutionize how scientists design stronger, more resilient materials, potentially impacting industries from aerospace to energy infrastructure.

The term of the appointment is two years, with the option to extend to a third year depending on performance and funding availability.

What You Need

Minimum Job Requirements:


  • Excellent understanding of cutting edge machine learning architectures and algorithms, with a strong ability to design, analyze, and optimize models for scientific problems.
  • Hands-on experience training machine learning models with PyTorch, JAX, or TinyGrad
  • Strong track record as evidenced by publications in high impact journals and top-tier ML conferences

Education/Experience: A Ph.D. degree in a STEM field such as Computer Science, Data Science, Applied Mathematics, Computational Physics, Engineering, or a related STEM field. For a postdoctoral appointment the candidate must have completed all Ph.D. requirements by commencement of the appointment and must be within five years of completion of the Ph.D.

Desired Qualifications:

  • Experience with training machine learning models on supercomputing platforms, utilizing multiple nodes, and optimizing parallelization for large-scale AI workloads.
  • Experience with optimization techniques for large-scale AI models, including mixed precision training, model parallelism, and distributed training strategies.
  • Proficiency with machine learning libraries and frameworks such as Hugging Face Transformers and Datasets, DeepSpeed, PyTorch Lightning, Weights & Biases, among others.

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.

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.

Note to Applicants:

Please note that no applicant is expected to have all the desired skills. Anyone who meets the minimum requirements is encouraged to apply.

To apply, submit your online application including your CV and a one-page cover letter. Please note that applications submitted without a cover letter will not be considered. Exceptional candidates may also be considered for prestigious fellowships at LANL.

For general information about being a LANL postdoc, visit the Postdoc Program website.
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.

Los Alamos is a beautiful, high-altitude town offering a vibrant community of world-class researchers and proximity to outdoor recreational opportunities like skiing, mountain biking, rock climbing (traditional, sport, and bouldering), camping, hiking, rafting, and more-all just minutes away.

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, 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 applyhelp@lanl.gov or call 1-505-664-6947 option 2 and then option 3.