Master's Thesis – AI for Acoustic Simulation
Core
Developing AI-driven Reduced Order Models to accelerate computationally expensive 3D acoustic simulations, specifically for automotive cabin acoustics.
Role type
Master's thesis intern in AI for acoustic simulation
Builds
AI-enabled workflows for industrial simulation and acoustic analysis
Domain
Automotive engineering, acoustics, machine learning
Deliverable
production ML models
Required skills
acoustics knowledge, Finite Element Method, numerical 3D simulation, AI/Machine Learning applications in engineering, analytical problem-solving
Preferred skills
familiarity with Siemens Simcenter tools, curiosity about AI in engineering
Technologies
Siemens Simcenter, AI transformer models, 3D finite element analysis
Responsibilities
configure training models for generating Reduced Order Models, investigate sensitivity of AI transformer model inputs/outputs, collaborate with development and application teams on real engineering use cases, evaluate innovative AI-enabled workflows for industrial simulation
Seniority
Master's student, research-focused