Sandia National Laboratories Postdoctoral Appointee - Machine Learning for Material Mechanics in Albuquerque, New Mexico
This postdoctoral position is a temporary position for up to one year, which may be renewed at Sandia's discretion up to five additional years. The PhD must have been conferred within five years prior to employment. Individuals in postdoctoral positions may bid on regular Sandia positions as internal candidates, and in some cases may be converted to regular career positions during their term if warranted by ongoing operational needs, continuing availability of funds, and satisfactory job performance.
Employees must remain in their current position for one year before applying for a new position, with the exception of student interns. Application of this requirement will not supersede collective bargaining agreements. See collective bargaining labor agreements for represented bidder eligibility requirements for represented employees.
Are you looking to join a team that solves significant issues for our nation’s security? The Materials and Failure Modeling Department is looking for a highly motivated and productive individual to work in a dynamic multidisciplinary teaming environment with a focus on the prediction of material behavior in various environments! A key thrust is the connection of process-structure-property-performance relationships across a range of materials, structures, and manufacturing processes. The individual’s work portfolio would be expected to cover a spectrum of work spanning the entire research-development-application's domain. There are significant opportunities to team with in-house code development teams and material scientists, as well as daily opportunities to work on very challenging problems utilizing world-class computational resources. In this role, the successful candidate will have the opportunity to:
Work in collaboration with subject matter experts at Sandia on the development of modeling approaches to predict material behavior, including failure, using both traditional Solid Mechanics and emerging machine learning methods.
Develop accelerated predictive capabilities, such as neural networks or parallel time integration, to model the metal Additive Manufacturing process with an emphasis on Solid Mechanics outcomes including residual stress and distortion.
Work closely with other subject matter experts in the areas of computational and experimental mechanics.
Partner with multi-physics code development teams to drive technical innovation to robust predictive capabilities.
Apply the principles of material mechanics and advanced computational finite-element analysis to provide credible solutions to engineering problems.
Collaborate with both internal and external partners to develop new research opportunities.
Publish research findings in peer-reviewed journals.
Join our team and achieve your dreams while making a difference!
PhD in Mechanical Engineering, Applied Mechanics, Aerospace Engineering, Civil Engineering, or related field
R&D experience of solid mechanics, including strength of materials, continuum mechanics, and material mechanics
Experience of nonlinear material behavior, fracture mechanics and material failure modeling, computational mechanics, and computer programming
Experience in computer programming and code development with one or more object-oriented languages such as Python, C++, etc.
Excellent written and oral communication skills as evidenced by conference presentations and journal publications
Ability to obtain and maintain a DOE Q clearance
Knowledge and experience in metal Additive Manufacturing, including process and performance modeling
Experience with machine learning techniques such as classification and regression and working knowledge of one or more common machine learning platforms such as Tensorflow, Pytorch, Keras or Scikit-learn
Knowledge and experience of experimental techniques for material characterization
Experience in performing finite element simulations of materials and structures subjected to complex and extreme loading conditions, up to and including failure modeling
Knowledge of probability theory and uncertainty quantification methodology
The Materials and Failure Modeling Department 1558 performs material mechanics R&D, develops advanced engineering models, and deploys state-of-the-art computational capabilities to enable physically credible prediction of material behavior and failure in support of Sandia’s mission. Focus areas of the department include adaptive material and failure models, robust computational material library covering events from aging to shock physics, effective model calibration methodologies, and quantification of margin and uncertainty of material models.
Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. Some of the main reasons we love our jobs:
Challenging work with amazing impact that contributes to security, peace, and freedom worldwide
Some of the best tools, equipment, and research facilities in the world
Career advancement and enrichment opportunities
Flexible work arrangements for many positions include; 9/80 (work 80 hours every two weeks with every other Friday off) and 4/10 (work 4 ten-hour days each week) compressed workweeks, part-time work and telecommuting (a mix of onsite work and working from home)
Generous vacations, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*
World-changing technologies. Life-changing careers. Learn more about Sandia at: http://www.sandia.gov
*These benefits vary by job classification.
Sandia is required by DOE to conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. If you hold more than one citizenship (i.e., of the U.S. and another country), your ability to obtain a security clearance may be impacted.
Applicants offered employment with Sandia are subject to a federal background investigation to meet the requirements for access to classified information or matter if the duties of the position require a DOE security clearance. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause a clearance to be denied or terminated by DOE, resulting in the inability to perform the duties assigned and subsequent termination of employment.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status and any other protected class under state or federal law.
Sandia demonstrates its commitment to public safety in the national interest by requiring that all new hires attest to their vaccination status before commencing employment. The requirement also applies to those who are telecommuting and working virtually.
Any concerns about the ability to meet this requirement should be directed to HR Solutions at (505) 284-4700.