As part of our CATIA Function Driven Generative Design and SIMULIA Structural Generative Engineer portfolios, you will contribute to the integration of AI-based surrogate models to accelerate the design process and enhance simulation performance.

Role Description & Responsibilities

• Research, design, and implementation of AI-driven methods for structural optimization and simulation, advancing next-generation generative engineering capabilities
• You will collaborate with cross-functional teams to define, design, and deliver innovative software features within our engineering simulation portfolio
• You will stay at the forefront of emerging trends in finite element analysis, optimization, and AI applications in engineering, contributing to knowledge sharing within a globally distributed R&D team

Qualifications

• Ideally, a completed bachelor’s degree in mathematics, computer science, mechanical engineering or similar areas of study
• First experience with Computer-Aided Engineering (CAE) & Finite Element Methods (FEM) in theory as well as preferably in practice
• Understanding and knowledge in mechanics, mathematics, and/or artificial intelligence architecture such as surrogate models
• Programming skills in Python, C++ or Fortran are advantageous
• Fascination for (simulation-based) optimization
• Very good English language skills in speaking and writing, German language skills are advantageous

What's in it for you

• Flexible working hours with the possibility to work partially outside the office
• Learning from and working with highly qualified, dedicated and diverse teams
• Additional benefits & perks such as Urban Sports Club membership (because who doesn't love staying fit while having fun?) and of course, unlimited coffee, fruit, and drinks at the office, we’ve got you covered ;)