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Postdoctoral Appointee – Mechanical Engineering

Argonne

·

Yesterday

Salary
$73k – $121k
Location
Lemont, IL USA, United States of America
Workplace
Onsite
Type
Full-time
Department
Engineering
Education
PhD
Source
Workday

Description

Argonne National Laboratory, in the Applied Materials Division, has an immediate opening for a postdoctoral appointee.   The candidate will develop physics-based models to predict the structure and performance of materials under extreme conditions.

 

The candidate will work with a multidisciplinary team to develop models in the MOOSE multiphysics finite element framework.  These models will include processing to structure models of additively manufactured metallic and ceramic materials and structure to performance models based on the crystal plasticity finite element method and similar micromechanical theories.  The candidate will also be expected to apply these models to predict the engineering behavior of materials in service environments.

Position Requirements

  • Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, structural engineering, or a closely related field.
  • Expertise in formulating and implementing micromechanical models, ideally including crystal plasticity methods.
  • Good grasp of numerical methods for implementing and solving complex physics-based models in the context of the finite element method.
  • Coding experience in C++ and/or python is required, along with the responsible use of AI-assisted coding tools.
  • Strong skills in oral and written communications and presentations.
  • A successful candidate must have the ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
  • This position requires an on-site presence at the Argonne campus in Lemont, Illinois, five days per week.

 

Preferred Qualifications:

  • Experience using the MOOSE simulation framework is highly desired.
  • Experience fitting complicated physics-based models against test data, including machine learning and Bayesian optimization approaches.
  • Specific experience modeling the performance of advanced engineering ceramics and/or the high temperature performance of metal alloys.

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

The expected hiring range for this position is $72,879.00-$121,465.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.  

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis.  Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements.  Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

Skills

PythonMachine Learning

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