| Location | Johnston, RI |
| Industry | Computer Software |
| Year Founded | 1981 |
| Website | http://www.3ds.com/ |
Role Description & Responsibilities
Do you have a passion for multiphysics simulation, data integrity, and AI-driven engineering workflows? Join us to help validate and enable next-generation machine learning models built on high-fidelity simulation data within the 3DEXPERIENCE platform.
In this role, you will operate at the intersection of finite element analysis (FEA), data preparation, and AI model validation, ensuring that historical simulation datasets are accurate, consistent, and production-ready for machine learning applications.
You will work primarily within GUI-driven workflows on cloud-based HPC environments to execute, validate, and prepare simulation data used to power predictive engineering and design optimization.
Key Responsibilities
Execute and validate physics-based simulations using the 3DEXPERIENCE platform environment
Review and validate historical FEA datasets for:
Boundary condition correctness
Mesh quality and convergence behavior
Material model consistency
Prepare and transform simulation outputs into structured datasets for machine learning training:
Feature extraction
Normalization and consistency checks
Label validation
Perform regression and validation testing on simulation workflows and datasets
Compare simulation outputs against baseline or "gold standard" datasets to ensure fidelity
Identify and debug issues in simulation execution across cloud HPC environments (job failures, convergence issues, runtime errors)
Collaborate with R&D team members in Product Define, and Development to ensure high-quality training data pipelines
Support development of surrogate models by validating ML predictions against physics-based results
Document test methodologies, validation criteria, and data preparation workflows
Qualifications
Master's or PhD degree in:
Mechanical Engineering
Aerospace Engineering
Applied Physics
Computational Engineering or related field
0-3+ years of experience in simulation, CAE, or engineering software environments
Hands-on experience with at least one FEA tool
Strong understanding of:
Finite Element Analysis fundamentals
Boundary conditions, meshing, and solver behavior
Numerical accuracy and convergence
Experience working with engineering datasets and structured data
Excellent English verbal and written communication skills
Preferred Qualifications
Experience using the 3DEXPERIENCE platform
Exposure to machine learning workflows or data pipelines
Familiarity with Python (NumPy, Pandas) for data processing
Experience running simulations in cloud or HPC environments (e.g., job scheduling, distributed compute)
Understanding of:
Surrogate modeling
Reduced-order modeling
Design optimization workflows
Experience with test case design, validation strategies, and regression testing in numerical systems