Materials Science Postdoc for 3D Imaging and Mechanics of Metallic Foam and Cellular Materials
- Req. Number: IRC146353
- Organization : MST-8 / Structure/Property Relations
- City, State: Los Alamos, New Mexico
What You Will Do
The Materials Science in Radiation and Dynamic Extremes Group (MST-8) is seeking a Materials Science Postdoctoral Research Associate to conduct research at the intersection of three-dimensional imaging, mesoscale modeling, and generative artificial intelligence (AI) to investigate the dynamic response of metallic foams and cellular materials.
This position is part of a newly funded project to develop adaptive, physics-constrained generative diffusion models that act as real-time digital twins of complex, time-varying systems observed through sparse measurements. For metallic foams and cellular materials subjected to dynamic compression and shock loading, a central challenge is to determine how their three-dimensional architecture including pore size, shape, and distribution; cell wall thickness, ligament connectivity; and structural defects controls deformation, collapse, damage and energy absorption. These mechanisms evolve rapidly across micrometer-scale features within millimeter-scale samples. Dynamic experiments typically provide only sparse and indirect observations such as a limited number of ultra-fast 2D detector images or 1D photon Doppler velocimetry (PDV) traces.
This project will combine these measurements with mechanics-based constraints and mesoscale simulations to reconstruct the evolving three-dimensional cellular architecture and associated density, deformation, velocity, stress, and damage fields; quantify uncertainty in the reconstructed states; and predict their subsequent evolution. The resulting capabilities will support adaptive, closed-loop 4D imaging experiments and provide otherwise inaccessible insight into mechanisms such as cell-wall bending and buckling, ligament fracture, localized pore collapse, compaction-front propagation, and densification. Ultimately, the work will establish quantitative relationships among initial cellular architecture, local collapse mechanisms, and macroscopic properties such as strength, failure resistance, and energy absorption under dynamic loading.
The successful candidate will:
Experimental resources and collaborations include the Advanced Photon Source (APS) at Argonne National Laboratory, the Dynamic Compression Sector (DCS), experimental facilities at Los Alamos National Laboratory, and university collaborators. The successful candidate will join a multidisciplinary team of materials scientists, experimental physicists, applied mathematicians, computer scientists, and theorists from across LANL.
What You Need
Minimum Job Requirements:
Desired Qualifications:
Work Environment:
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:
As part of the application process, please upload your CV, a cover letter detailing work interest and qualifications, and names of three references. Contact Dr. Reeju Pokharel (reeju@lanl.gov) and Michael Hargather (mjh@lanl.gov) for more details. The review process will begin immediately and continue until the position is filled. Note that US citizenship is not a requirement.
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:
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.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:
The Materials Science in Radiation and Dynamic Extremes Group (MST-8) is seeking a Materials Science Postdoctoral Research Associate to conduct research at the intersection of three-dimensional imaging, mesoscale modeling, and generative artificial intelligence (AI) to investigate the dynamic response of metallic foams and cellular materials.
This position is part of a newly funded project to develop adaptive, physics-constrained generative diffusion models that act as real-time digital twins of complex, time-varying systems observed through sparse measurements. For metallic foams and cellular materials subjected to dynamic compression and shock loading, a central challenge is to determine how their three-dimensional architecture including pore size, shape, and distribution; cell wall thickness, ligament connectivity; and structural defects controls deformation, collapse, damage and energy absorption. These mechanisms evolve rapidly across micrometer-scale features within millimeter-scale samples. Dynamic experiments typically provide only sparse and indirect observations such as a limited number of ultra-fast 2D detector images or 1D photon Doppler velocimetry (PDV) traces.
This project will combine these measurements with mechanics-based constraints and mesoscale simulations to reconstruct the evolving three-dimensional cellular architecture and associated density, deformation, velocity, stress, and damage fields; quantify uncertainty in the reconstructed states; and predict their subsequent evolution. The resulting capabilities will support adaptive, closed-loop 4D imaging experiments and provide otherwise inaccessible insight into mechanisms such as cell-wall bending and buckling, ligament fracture, localized pore collapse, compaction-front propagation, and densification. Ultimately, the work will establish quantitative relationships among initial cellular architecture, local collapse mechanisms, and macroscopic properties such as strength, failure resistance, and energy absorption under dynamic loading.
The successful candidate will:
- Develop and perform mesoscale continuum-mechanics and shock-physics experiments and simulations of metallic foams and cellular materials under quasi-static and high-strain-rate, and shock-compression loading.
- Curate, process, and analyze existing experimental datasets, including X-ray phase-contrast imaging (PCI) and PDV measurements from dynamic-compression experiments.
- Integrate experimental observations with simulation results to construct datasets for generative AI-enabled surrogate model development and to establish quantitative relationships among initial cellular architecture, local collapse mechanisms, and macroscopic mechanical response.
- Identify and formulate appropriate physical constraints for incorporation into generative models including conservation of mass, momentum, and energy. Collaborate closely with AI/ML researchers to develop, train, and validate physics-constrained latent diffusion models using simulated and experimental data.
- Develop validation and observation criteria to quantify reconstruction accuracy and uncertainty and determine the number, type, spatial resolution, and temporal resolution of measurements needed to recover the evolving three-dimensional cellular structure and physical state.
- Help design, propose, and conduct new in situ and dynamic compression experiments at Department of Energy X-ray light sources and LANL shock physics facilities.
- Contribute to the development and demonstration of real-time inference, adaptive measurement selection, and closed-loop experimental-feedback capabilities.
- The project team already has extensive expertise in AI and machine learning. The primary need for this position is therefore a strong foundation in the solid mechanics, shock physics, and experimental or computational characterization of metallic foams, cellular solids, porous materials, or related heterogeneous material systems. Of particular interest is experience connecting 3-D architecture to deformation, collapse, damage, wave propagation, densification, and macroscopic mechanical response. Candidates with strong computational skills and an interest in working closely with AI/ML researchers to translate materials physics into model constraints, training data, and validation criteria are strongly encouraged to apply.
Experimental resources and collaborations include the Advanced Photon Source (APS) at Argonne National Laboratory, the Dynamic Compression Sector (DCS), experimental facilities at Los Alamos National Laboratory, and university collaborators. The successful candidate will join a multidisciplinary team of materials scientists, experimental physicists, applied mathematicians, computer scientists, and theorists from across LANL.
What You Need
Minimum Job Requirements:
- Strong foundation in materials science, solid mechanics or shock physics with knowledge of elasticity, plasticity, damage and failure, wave propagation, and structure property relationships in cellular, porous, or heterogeneous materials.
- Demonstrated research experience in at least three of the following areas: continuum-mechanics or shock-physics simulation; experimental mechanics or materials characterization; X-ray imaging or dynamic diagnostics; and quantitative image or data analysis.
- A PhD in Materials Science and Engineering, Mechanical Engineering, Engineering Mechanics, Applied Physics, Physics or a closely related field, completed within the last three years or anticipated to be completed before the start date.
- Demonstrated experience in developing or using scientific simulation software and data analysis workflows using a scientific programming language such as Python, Fortran, C/C++, or Matlab.
- Demonstrated experience in quantitative analysis of computational or experimental datasets and interpreting results in terms of underlying materials behavior.
- Interest in integrating mechanics-based models and experimental measurements with machine learning and other data-driven methods.
- Excellent communication skills (both oral and written), as evidenced by publications and presentations, and the ability to work effectively in a multidisciplinary team.
- Willingness to participate in experiments at national laboratory and user facilities and to travel for multiday experiments at beamlines.
Desired Qualifications:
- Experience studying metallic foams, cellular solids, porous materials, architected materials or other heterogeneous material systems, including relationships among three-dimensional architecture, local deformation mechanisms, and macroscopic mechanical response.
- Experience modeling the quasi-static, high-strain-rate or shock response of materials using finite-element, hydrocode, or related continuum-mechanics methods.
- Knowledge of constitutive modeling of porous compaction, plasticity, damage and fracture, contact, and equation of state.
- Hands-on experience planning, conduction or supporting quasi-static, high-strain-rate, or shock-compression experiments, and performing post experiment analysis.
- Experience with dynamic diagnostics such as PDV, high-speed optical imaging, X-ray phase contrast imaging, or time-resolved X-ray radiography.
- Experience with 3D imaging techniques such as X-ray computed tomography for initial state characterization and image processing methods such as reconstruction, segmentation, registration, feature extraction, and quantitative morphological analysis.
- Experience writing beamtime proposals and carrying out experiments at synchrotron or XFEL user facilities, and willingness to travel for multi-day beamtimes.
- Experience with uncertainty quantification, data assimilation, inverse problems, numerical methods and high-performance computing including GPU computing and analysis of large-scale simulation or experimental datasets.
Work Environment:
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:
As part of the application process, please upload your CV, a cover letter detailing work interest and qualifications, and names of three references. Contact Dr. Reeju Pokharel (reeju@lanl.gov) and Michael Hargather (mjh@lanl.gov) for more details. The review process will begin immediately and continue until the position is filled. Note that US citizenship is not a requirement.
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)
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.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:
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