Data-driven and Machine Learning Postdoctoral Research Associate
- Req. Number: IRC142140
- Organization : Computational Physics and Methods (CAI-2)
- City, State: Los Alamos, New Mexico
What You Will Do
The Computational and Physics Methods Group (CAI-2) in the Computing and Artificial Intelligence Division at Los Alamos National Laboratory is seeking a skilled and driven researcher for a postdoctoral position at the intersection of applied mathematics, data-driven modeling of dynamical systems, and machine learning.
The successful candidate will join a multidisciplinary team of mathematicians, physicists, and machine learning researchers advancing AI-enabled modeling of complex dynamical systems. Leveraging transfer operator theory (e.g., Koopman and Perron-Frobenius methods), the postdoc will develop novel learning architectures that both respect physical constraints and help discover underlying structure from data. Core activities will span method development, theoretical analysis, and empirical validation at scale on benchmark and mission-relevant datasets. The position offers exposure to multiple application domains (e.g., wildfire, ocean, and space weather), as well as opportunities for cross-disciplinary collaboration, scientific workshop organization, and conference participation.
What You Need
Minimum Job Requirements:
Education/Experience: PhD in Applied Mathematics, Computational or Statistical Physics, Applied Statistics, Computer Science, or a related field completed within the last 5 years or to be completed soon.
Desired Qualifications:
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.
For full consideration please include:
• A comprehensive CV with publication list
• A cover letter describing your qualifications and how you meet the job requirements
• Contact information for at least three professional references.
For questions about this position contact: Derek DeSantis (ddesantis@lanl.gov) or Yen Ting Lin (yentingl@lanl.gov).
For more information, visit LANL career page: https://www.lanl.gov/careers/index.php.
Outstanding candidates may be considered for a Director's Postdoc Fellowship. For more information about the Postdoc Program, go to: https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php
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:
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.
The Computational and Physics Methods Group (CAI-2) in the Computing and Artificial Intelligence Division at Los Alamos National Laboratory is seeking a skilled and driven researcher for a postdoctoral position at the intersection of applied mathematics, data-driven modeling of dynamical systems, and machine learning.
The successful candidate will join a multidisciplinary team of mathematicians, physicists, and machine learning researchers advancing AI-enabled modeling of complex dynamical systems. Leveraging transfer operator theory (e.g., Koopman and Perron-Frobenius methods), the postdoc will develop novel learning architectures that both respect physical constraints and help discover underlying structure from data. Core activities will span method development, theoretical analysis, and empirical validation at scale on benchmark and mission-relevant datasets. The position offers exposure to multiple application domains (e.g., wildfire, ocean, and space weather), as well as opportunities for cross-disciplinary collaboration, scientific workshop organization, and conference participation.
What You Need
Minimum Job Requirements:
- Experience in data-driven and/or ML methods for dynamical systems, as evidenced through a strong scientific record of peer-reviewed publications and presentations.
- Fundamental understanding of the Koopman and/or Perron-Frobenius Operators.
- Excellent scientific programming skills with demonstrated, hands-on experience (beyond online courses/certifications) using modern ML libraries and tools-e.g., PyTorch and/or JAX-as well as high-level languages such as Python (including NumPy/SciPy).
- Strong mathematical training in at least one relevant field (e.g., functional analysis/operator theory, probability/stochastic processes, numerical analysis/scientific computing, and/or optimization/ML theory).
- Ability to work both independently and collaboratively in an interdisciplinary environment.
- Ability to communicate technical results clearly in writing and presentations.
- Demonstrated creativity and interest in developing new research directions and original methodologies.
Education/Experience: PhD in Applied Mathematics, Computational or Statistical Physics, Applied Statistics, Computer Science, or a related field completed within the last 5 years or to be completed soon.
Desired Qualifications:
- Prior research experience directly involving the Koopman and/or Perron-Frobenius operators.
- Prior research experience developing and/or implementing neural operators.
- Strong background in functional analysis/operator theory, including spectral theory, reproducing kernel Hilbert space methods, and the approximation of infinite-dimensional systems by finite-dimensional models.
- Experience with probabilistic modeling and uncertainty quantification (e.g., Bayesian deep learning, generative models, variational inference, ensembles, probabilistic scoring rules).
- Experience developing novel neural network architectures (e.g., customized loss functions, complex network topologies, constrained or structure-preserving architectures).
- Experience working with large numerical simulations or high-dimensional datasets and familiarity with high-performance computing environments (e.g., clusters, GPUs, job schedulers).
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.
For full consideration please include:
• A comprehensive CV with publication list
• A cover letter describing your qualifications and how you meet the job requirements
• Contact information for at least three professional references.
For questions about this position contact: Derek DeSantis (ddesantis@lanl.gov) or Yen Ting Lin (yentingl@lanl.gov).
For more information, visit LANL career page: https://www.lanl.gov/careers/index.php.
Outstanding candidates may be considered for a Director's Postdoc Fellowship. For more information about the Postdoc Program, go to: https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php
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)
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.
