Postdoctoral Appointee – Mechanical Engineering
Argonne National Laboratory
Lemont, USA
Job posting number: #7278162 (Ref:418900)
Posted: September 6, 2024
Job Description
The Applied Materials Division at Argonne National Laboratory has an immediate opening for a postdoctoral appointee. The candidate will develop material models and finite element models for a variety of manufacturing processes. The candidate will also develop reduced-order models and use machine learning techniques to assist model calibration.
The candidate will work with a multidisciplinary team to develop material models and finite element models for a variety of manufacturing processes including infiltration, sintering, debinding, welding, post-build treatments, etc. relying on both physics-based simulations and data-driven approaches. The candidate will also work closely with industry partners to develop reduced-order models for the manufacturing processes, which will be used to optimize process parameters for energy savings and decarbonization. The candidate will help draft and publish technical reports and journal publication describing the research outcome and will be expected to attend and present at technical conferences.
Position Requirements
Ph.D. in mechanical engineering, materials science, civil engineering, computer science, or a closely related field.
Experience with the finite element method.
Experience with reduced-order modeling.
Proficient in C++ and Python.
Skilled in Unix-based operating systems.
Skilled in oral and written communications and presentations at all levels of the organization.
Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
Ability to make our laboratory a safe, welcoming, inclusive, and accessible environment where all can thrive.
Preferred qualifications:
Experience with MOOSE.
Experience with PyTorch, JAX, or TensorFlow.
Job Family
Postdoctoral FamilyJob Profile
Postdoctoral AppointeeWorker Type
Long-Term (Fixed Term)Time Type
Full timeAs an equal employment opportunity and affirmative action employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, gender expression, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other 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.
Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
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