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Simulation Engineer, Computational Mechanics - Redmond, United States - META
Description
We are seeking an experienced simulation engineer with a strong background in computational methods, machine learning, and material science.Candidate will use computational methods to speed up the development of novel materials targeting specific mechanical and thermal properties, and develop models and test plans to evaluate relevant properties once the novel materials are synthesized.
Our ideal candidate approaches complex problems with an analytical mindset firmly rooted in scientific first principles. They are unafraid to challenge underlying assumptions and are dedicated to delivering solutions in addition to insight.We want someone who works well in a highly collaborative, cross-functional environment, can drive clarity from ambiguity, communicates complex concepts clearly, and is unafraid to tackle new challenges.
Simulation Engineer, Computational Mechanics ResponsibilitiesDeliver simulation and ML based solutions to enable development of new materials targeting specific mechanical and thermal properties.
Devise and implement plans for mechanical characterization and reliability assessments of novel materials.Collaborate with researchers and cross-functional partners to identify and mitigate risks related to new materials, conduct validation tests, and deliver objective, data-driven engineering guidance and solutions.
Organize and lead design reviews, solution brainstorms, and implementation efforts.Present results in a form actionable by cross-functional team members and leadership.
Minimum QualificationsPhD degree or equivalent experience in Computational Mechanics, Computational Physics, Computational Material Science, Applied Mathematics, or a related field.
Experience using simulation for failure analysis, material characterization, and reliability assessment.Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view.
Experience with machine learning, and physics-informed machine learning.
Experience building relationships and working cross-functionally with multidisciplinary teams.5+ years experience developing high quality simulation-based solutions for consumer products.5+ years experience using FEA simulation tools such as COMSOL, Ansys and/or Abaqus.
Preferred QualificationsKnowledge of optics, CFD, heat transfer, acoustics is a plus.Experience using/developing DFT codes (e.g., VASP, FHI-aims), MD codes (e.g., LAMMPS, HOOMD), or related computational methods for material discovery.
Familiarity with material characterization techniques such as SEM, DMA, DSC, XRD, and fractography.
Experience with machine learning platforms such as PyTorch or TensorFlow.
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