Postdoctoral Research Associate in Stochastic Sensitivity Analysis for Multi-Physics Problems - Los Alamos National Laboratory
Los Alamos, NM
About the Job
What You Will Do
Come join the brightest minds at the most innovative R&D facility supporting National Security! The Computational Physics and Methods Group (CCS-2) at Los Alamos National Laboratory is seeking a Postdoctoral Research Associate to join our team for a new funded project. CCS-2 conducts application-focused methods research across a wide variety of computational physics areas including astrophysics, climate science, radiation transport, shock hydrodynamics, turbulent flows and machine learning and develops software for high-performance computing environments.
The successful candidate will develop and implement novel stochastic sensitivity analysis and uncertainty quantification methods for multi-physics problems of interest to LANL. The fundamental research will involve (1) development of stochastic sensitivity methods, using machine learning and artificial intelligence (AI) models, for estimating the sensitivity of multi-physics models, (2) development and implementation of uncertainty quantification tools to estimate the propagation of probability distribution in complex multi-scale coupled models. The methods will be applied to the modeling and control of multi-physics systems across scales and/or under extreme regimes. The successful candidate will work in a multidisciplinary team in a collaborative environment and interact with scientists working in numerical methods, applied mathematics, data science, machine learning, and experimental design in different organizations of the Laboratory. In collaboration with LANL staff scientists, they will contribute to LANL's projects, and produce results that can be published in the scientific literature and presented at technical conferences.
What You Need
Minimum Job Requirements:
Education/Experience: A PhD in applied mathematics, physics, engineering, or related fields, completed within the last five years or soon to be completed.
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.
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 https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php .
Note to Applicants:
When applying on-line, please include the following files with your application: a CV (please include month/year of PhD) and a detailed cover letter describing the candidate's interest and qualifications in this research area. For questions or clarification regarding this position, please contact Humberto C Godinez (hgodinez@lanl.gov) or Nishant Panda (nishpan@lanl.gov).
Fellowship Opportunities: Candidates may be considered for a Director's Fellowship, CNLS Fellowship or Nicholas C. Metropolis Fellowship. For the named fellowship, the research scope can be broadened to include any topic of mutual interest.
Postdoctoral positions are for 2 years, with a potential for a renewal for a third year.
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.
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.
Come join the brightest minds at the most innovative R&D facility supporting National Security! The Computational Physics and Methods Group (CCS-2) at Los Alamos National Laboratory is seeking a Postdoctoral Research Associate to join our team for a new funded project. CCS-2 conducts application-focused methods research across a wide variety of computational physics areas including astrophysics, climate science, radiation transport, shock hydrodynamics, turbulent flows and machine learning and develops software for high-performance computing environments.
The successful candidate will develop and implement novel stochastic sensitivity analysis and uncertainty quantification methods for multi-physics problems of interest to LANL. The fundamental research will involve (1) development of stochastic sensitivity methods, using machine learning and artificial intelligence (AI) models, for estimating the sensitivity of multi-physics models, (2) development and implementation of uncertainty quantification tools to estimate the propagation of probability distribution in complex multi-scale coupled models. The methods will be applied to the modeling and control of multi-physics systems across scales and/or under extreme regimes. The successful candidate will work in a multidisciplinary team in a collaborative environment and interact with scientists working in numerical methods, applied mathematics, data science, machine learning, and experimental design in different organizations of the Laboratory. In collaboration with LANL staff scientists, they will contribute to LANL's projects, and produce results that can be published in the scientific literature and presented at technical conferences.
What You Need
Minimum Job Requirements:
- Experience and strong track record in sensitivity analysis methods, such as adjoint sensitivity
- Proficient in machine learning and AI models
- Proficient in statistical methods and probability theory
- Ability to conduct independent and collaborative research in a multi-disciplinary environment
- Programming experience, preferably in Python, Fortran, or C/C++
- Excellent oral and written communication skills
Education/Experience: A PhD in applied mathematics, physics, engineering, or related fields, completed within the last five years or soon to be completed.
Desired Qualifications:
- Experience using AI models useful for probability distributions, such as diffusion models, normalizing flows, and generative models
- Experience with adjoint modeling and/or automatic differentiation tools
- Knowledge and proficiency in Koopman and Perron-Frobenius operator theory
- Experience with deep learning and tensor libraries such as PyTorch
- Ability to meet the tight schedules, organize and prioritize tasks for effective achievements of project goals
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. For more information go to Postdoc Program website at https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php .
Note to Applicants:
When applying on-line, please include the following files with your application: a CV (please include month/year of PhD) and a detailed cover letter describing the candidate's interest and qualifications in this research area. For questions or clarification regarding this position, please contact Humberto C Godinez (hgodinez@lanl.gov) or Nishant Panda (nishpan@lanl.gov).
Fellowship Opportunities: Candidates may be considered for a Director's Fellowship, CNLS Fellowship or Nicholas C. Metropolis Fellowship. For the named fellowship, the research scope can be broadened to include any topic of mutual interest.
Postdoctoral positions are for 2 years, with a potential for a renewal for a third year.
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.
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.
Source : Los Alamos National Laboratory