1+ months

Computational Optimization Engineer - Postdoctoral Researcher

Lawrence Livermore National Laboratory
Livermore, CA 94550

We have an opening for a Computational Engineer to conduct basic and applied research in the optimization, simulation, and design of physical and engineered systems. You will work collaboratively and independently to extend and develop physics-based design optimization tools. The team is working to both extend the state-of-the-art and support Laboratory missions. This position is in the Computational Engineering Division (CED).

In this role you will

  • Develop and implement HPC algorithms and simulations for the optimal design of engineering systems governed by nonlinear, transient, multiscale, and multiple physical phenomena that include uncertainties in geometry and material properties.
  • Contribute to solving challenging design optimization problems.
  • Develop continuum-based finite element simulations to solve the governing partial differential equations of the physical systems that govern the design response.
  • Identify and solve challenging design optimization problems highlighting capabilities and establishing credibility with mission customers.
  • Document research through presentations and peer-reviewed journal articles and contribute to identifying future research directions and proposals that will provide opportunities in the field.
  • Perform other duties as assigned.

  • Ph.D. in Engineering, Mathematics, Computational Science, or a related field, or the equivalent combination of education and related experience.
  • Experience developing simulation tools using continuum approaches (e.g., finite elements) for physical systems.
  • Experience programming skill in C/C++/FORTRAN and scripting languages including Python/Matlab.
  • Knowledge of massively-parallel computing and one or more associated parallel programming interfaces, such as MPI, OpenMP, or CUDA.
  • Ability to perform independent research.
  • Proficient verbal and written communication skills needed to effectively collaborate in a team environment, present and explain technical information, document work, prepare and present successful proposals and high-quality research papers.

Qualifications We Desire

  • Knowledge of explicit design sensitivity analysis via direct (forward) and adjoint (backward) methods.
  • Knowledge of shape/topology optimization techniques and algorithms.
  • Exposure to machine learning and other data science techniques.

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years. Eligible candidates are those who have been awarded a PhD at time of hire date.

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Why Lawrence Livermore National Laboratory?

  • Included in 2022 Best Places to Work by Glassdoor!
  • Work for a premier innovative national Laboratory
  • Comprehensive Benefits Package
  • Flexible schedules (*depending on project needs)
  • Collaborative, creative, inclusive, and fun team environment

Learn more about our company, selection process, position types and security clearances by visiting our Career site.

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COVID-19 Vaccination Mandate

LLNL demonstrates its commitment to public safety by requiring that all new Laboratory employees be immunized against COVID-19 unless granted an accommodation under applicable state or federal law. This requirement will apply to all new hires including those who will be working on site, as well as those who will be teleworking.

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Security Clearance

This position requires either no security clearance, or a Department of Energy (DOE) L-level or Q-level clearance depending on the particular assignment.

If you are selected and a security clearance is required, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. In addition, all L or Q cleared employees are subject to random drug testing. L and Q-level clearances require U.S. citizenship.

If no security clearance is required, but your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. (This process does not apply to foreign nationals.)

For additional information, please see DOE Order 472.2.

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Pre-Employment Drug Test

External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

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Equal Employment Opportunity

LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

If you need assistance and/or a reasonable accommodation during the application or the recruiting process, please submit a request via our online form.

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California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.


Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States' security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is essential to innovation and creativity for continued success of the Laboratory's mission.

"},"jobDescription":{"title":"Job Description","text":"

We have an opening for a Computational Engineer to conduct basic and applied research in the optimization, simulation, and design of physical and engineered systems. You will work collaboratively and independently to extend and develop physics-based design optimization tools. The team is working to both extend the state-of-the-art and support Laboratory missions. This position is in the Computational Engineering Division (CED).

In this role you will

  • Develop and implement HPC algorithms and simulations for the optimal design of engineering systems governed by nonlinear, transient, multiscale, and multiple physical phenomena that include uncertainties in geometry and material properties.
  • Contribute to solving challenging design optimization problems.
  • Develop continuum-based finite element simulations to solve the governing partial differential equations of the physical systems that govern the design response.
  • Identify and solve challenging design optimization problems highlighting capabilities and establishing credibility with mission customers.
  • Document research through presentations and peer-reviewed journal articles and contribute to identifying future research directions and proposals that will provide opportunities in the field.
  • Perform other duties as assigned.
"},"qualifications":{"title":"Qualifications","text":"
  • Ph.D. in Engineering, Mathematics, Computational Science, or a related field, or the equivalent combination of education and related experience.
  • Experience developing simulation tools using continuum approaches (e.g., finite elements) for physical systems.
  • Experience programming skill in C/C++/FORTRAN and scripting languages including Python/Matlab.
  • Knowledge of massively-parallel computing and one or more associated parallel programming interfaces, such as MPI, OpenMP, or CUDA.
  • Ability to perform independent research.
  • Proficient verbal and written communication skills needed to effectively collaborate in a team environment, present and explain technical information, document work, prepare and present successful proposals and high-quality research papers.

Qualifications We Desire

  • Knowledge of explicit design sensitivity analysis via direct (forward) and adjoint (backward) methods.
  • Knowledge of shape/topology optimization techniques and algorithms.
  • Exposure to machine learning and other data science techniques.

Categories

Posted: 2022-04-28 Expires: 2022-07-30

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Computational Optimization Engineer - Postdoctoral Researcher

Lawrence Livermore National Laboratory
Livermore, CA 94550

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