Master's Thesis "Machine Learning Models for Data Preparation in Automotive CFD-Simulation Process"
Role details
Job location
Tech stack
Job description
Are you currently pursuing a master's degree with a technical focus and looking for a partner company to write your thesis?
Perfect! Magna Steyr is currently seeking a master's student to join us in the area of Computational Fluid Dynamics (CFD) and machine learning (ML).
The aim of this master's thesis is to speed up the data preparation process for complete vehicle CFD-simulation. Data preparation is the bottleneck in current industrial CFD processes. Preparing a complete vehicle geometry for external or internal flow investigation keeps an engineer busy for several days. To speed up data preparation, a machine learning model should be developed to automate some portions of this process (e.g., mesh cleaning, part classification). You will work together with CFD engineers as well as our machine learning experts and project engineers.
The following scopes should be included in your master's thesis:
- Conduct a literature review of previous works and define a schematic procedure.
- Prepare a training database in ANSA. Either from historical or public data.
- Research of various neural network architectures which can be considered for this application (e.g., 3D point- and mesh-based models).
- Create a first model and train it with previously created dataset. Optimize model setup if necessary.
- Create documentation and propose additional work to speed-up data preparation., * Everyday employee benefits, sport events, hiking and many other activities - Exclusively for you!
- Canteen, our café and shops - Our catering offers for you!
- Holistic health programs and multiple on-site consulting services - Magna supports!
- Sustainability Programs - Work and live responsibly!
Your profile matters! You will receive a monthly gross compensation of €700,-- for writing your master's thesis. Depending on your education and specific professional experience, there is a corresponding willingness to overpay.
Requirements
- Ongoing technical study at the university / university of applied sciences in mechanical engineering, automotive engineering, computer science or similar.
- A good understanding of Python coding and machine learning libraries (e.g., PyTorch, NumPy, TensorFlow) is essential.
- Basic knowledge and experience in the field of numerics and CFD are beneficial but not mandatory.
- Basics in Beta CAE Systems software package ANSA is advantageous but not necessary.
Your preferred qualifications
- Strong interest in bringing state-of-the-art machine learning to real world industry applications.
- High level of helpfulness and excellent communication skills.