Intern (m/f/d) - AI-Driven Optimization & Generative 3D MODSIM (Master's Thesis Option)
Core
Research and develop AI/ML multi-fidelity approaches for non-parametric optimization processes and structural optimization algorithms within finite element simulation.
Role type
Research intern (Master's Thesis option)
Builds
AI-driven generative design solutions for structural optimization
Domain
Mechanical/Civil/Aerospace engineering + AI/ML + Finite Element Method (FEM)
Deliverable
research
Required skills
Finite Element Method (FEM), structural mechanics, numerical methods, Python, C++, AI/ML fundamentals
Preferred skills
CAE experience, generative design knowledge, advanced Python/C++
Technologies
3DEXPERIENCE MODSIM, Tosca Structure, Abaqus, fe-safe, CATIA
Responsibilities
Develop AI/ML multi-fidelity approaches for optimization, implement structural optimization algorithms, prototype algorithmic routines in C++/Python, perform FEM modeling, evaluate cutting-edge AI/ML methods
Seniority
Intern
