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Physics Informed Machine Learning Jobs in New Mexico

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Physics Informed Machine Learning information

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in New Mexico? For Physics Informed Machine Learning jobs in New Mexico, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in New Mexico look for? The top searched job categories for Physics Informed Machine Learning jobs in New Mexico are:
Infographic showing various Physics Informed Machine Learning job openings in New Mexico as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Postdoctoral Research Associate in AI-Accelerated Molecular and Materials Modeling

Postdoctoral Research Associate in AI-Accelerated Molecular and Materials Modeling

Los Alamos National Laboratory

Los Alamos, NM

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


Los Alamos National Laboratory rating

9.2

Company rating: 9.2 out of 10

Based on 33 frontline employees who took The Breakroom Quiz

8th of 105 rated laboratories


Job description

What You Will Do
The Physics and Chemistry of Materials group (T-1) at Los Alamos National Laboratory seeks a highly motivated Postdoctoral Researcher to develop and apply advanced electronic structure, atomistic simulation, and AI/ML methodologies for understanding and controlling rare-earth element (REE) chemistry. The successful candidate will work at the intersection of quantum chemistry, machine learning, and reactive molecular simulations to investigate REE coordination, separation, and interfacial processes, while developing predictive computational tools that bridge atomistic mechanisms and experimentally observable properties. This position offers exceptional opportunities for cross-disciplinary collaboration, scientific workshop organization, and conference attendance.

What You Need
Minimum Job Requirements:
Education/Experience: Ph.D. in Chemistry, Physics, Materials Science, Chemical Engineering, or a related field completed within the last five years.
  • Experience with first-principles electronic structure methods, including DFT and/or TD-DFT.
  • Experience performing atomistic simulations of molecular and/or condensed-phase systems.
  • Experience with machine learning, data science, uncertainty quantification, or surrogate modeling for chemical systems.
  • Demonstrated ability to work creatively and independently as well as learn and collaborate with experts as a part of a multi-disciplinary team.
  • Excellent communication and writing skills, as evidenced by publications, cover letter and interview.

Desired Qualifications:
In addition to the minimum requirements, the following qualifications are desired, and preference will be given to candidates satisfying (at least one) of them:
  • Experience in separations science, coordination chemistry, and materials discovery.
  • Familiarity with molecular dynamics simulations, reactive chemistry, and automated reaction discovery.
  • Experience with advanced electronic structure methods such as CASSCF, GW/BSE, relativistic methods, or spin-orbit coupling treatments.
  • Knowledge of spectroscopy simulations, including X-ray, UV-Vis, Raman, or IR spectroscopy.
  • Experience developing or applying machine-learning interatomic potentials, reactive neural network potentials, or active-learning workflows.
  • Experience using high-performance computing platforms and large-scale scientific modeling.
  • Experience with model verification, validation, and uncertainty quantification, integration of simulation and experimental observations, and management of scientific datasets.
  • Experience in computer programming using modern computing languages. Programming skills in Python and/or scientific computing environments.
  • Demonstrated ability to work independently and with minimum supervision.
  • Willingness to work productively on multiple projects.
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:
  • The appointment is for a duration of two years, with the possibility of a third-year extension based on performance evaluation.
  • Candidates may be considered for a fellowship supported by the Center for Nonlinear Studies (CNLS). Outstanding candidates may be considered for a Director's Postdoc Fellowship or for the prestigious Richard P. Feynman, Darleane Christian Hoffman, J. Robert Oppenheimer, or Frederick Reines Distinguished Postdoc Fellowships.
  • For more information about the Postdoc Program, go to https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php
Contact:
  • Dr. Sergei Tretiak (serg@lanl.gov)
  • Dr. Arjen van Veelen (arjen.vanveelen@lanl.gov)
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.

426.2A:
This position is subject to DOE Order 426.2A, Personnel Selection, Training, and Qualification Requirements for DOE Nuclear Facilities, which establishes entry-level requirements to ensure candidates selected for specific positions can successfully perform the requirements of the job.
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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