Master's Thesis – AI for Acoustic Simulation

Master’s Thesis Intern – AI for Acoustic Simulation

Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, skyscrapers, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our Product Lifecycle Management software. We offer a role with responsibility, independence, and the possibility to contribute proactively, by encouraging a teamwork culture with room for individual development.

Strategic Student Program Belgium 2026

The Strategic Student Program is our formal internship program at Siemens Software globally. You will be mentored by experts and work directly with customers and technical teams to create direct business impact while gaining valuable professional experience. At Siemens, SSP interns gain access to an international student network and community, career development opportunities with professional growth pathways, practical training throughout the program, access to the Siemens Learning Hub and other training materials, and the opportunity to work on exciting projects within a global, diverse team.

Using AI-Driven Reduced Order Models

Using Machine Learning to develop Reduced Order Models is an innovative and transformative approach to accelerate complex and computationally expensive 3D numerical simulation. This methodology is actively being explored across a wide range of engineering disciplines and offers strong potential for industrial applications by enabling significantly faster turnaround times once models are properly trained.

What you’ll be doing as part of the Simcenter team in Belgium

Within Siemens Software, this thesis opportunity sits at the intersection of acoustic simulation, artificial intelligence, and advanced engineering workflows. You will work in close collaboration with both development and application teams to explore how the latest AI-based approaches can support next‑generation simulation use cases in automotive cabin acoustics.

Project description

During this master’s thesis, you will use Siemens Simcenter’s latest AI transformer model to explore workflows for training and generating AI-driven Reduced Order Models. You will investigate the benefits and challenges these models present in accelerating acoustic simulation, with a particular focus on automotive cabin acoustics.

Your work will contribute valuable practical insights into how AI-based Reduced Order Models can be applied to improve simulation efficiency while maintaining engineering relevance and quality.

What you will learn

• Master high‑fidelity 3D finite element‑based acoustic simulation using tools available in the Siemens Simcenter portfolio
• Explore workflows and configure training models for generating Reduced Order Models
• Investigate in depth the sensitivity of input and output characteristics of AI transformer models
• Collaborate with development and application teams on real engineering use cases
• Contribute to the evaluation of innovative AI‑enabled workflows for industrial simulation

What we’re looking for

We are looking for master’s students in Mechanical Engineering, Acoustics, Applied Physics, Computational Engineering, or a related field.

• Knowledge of acoustics and the Finite Element Method
• Familiarity with, or willingness to learn, numerical 3D simulation tools
• Curiosity and interest in Artificial Intelligence and Machine Learning applications in engineering
• Strong analytical and problem‑solving skills
• Good communication skills and proficiency in English
• A proactive mindset and eagerness to contribute to innovative engineering projects

What you’ll gain

• Hands‑on experience in advanced engineering software and simulation workflows
• Exposure to cutting‑edge applications of Artificial Intelligence in engineering
• Enhanced skills in acoustic simulation and 3D numerical analysis
• Insight into real‑world industrial engineering challenges
• The opportunity to contribute directly to Siemens Software’s innovation pipeline
• Collaboration with experienced experts across development and application engineering teams

SSP Belgium 2026, conditions & eligibility

This opportunity is planned as a 6‑month master’s thesis / internship collaboration based in Leuven, Belgium, within Siemens Software. The master’s thesis internship is conducted under the Belgian academic internship framework and, as such, is unpaid and not considered salaried employment. Interns will nevertheless enjoy the full Siemens Software Leuven experience, including access to the office gym, company events, technical presentations, the Siemen