Job
- Level
- Junior
- Job Field
- Software, Data
- Employment Type
- Part Time
- Contract Type
- Internship / school internship
- Salary
- from 700 € Gross/Month
- Location
- Graz
- Working Model
- Onsite
Job Summary
In this role, you will develop a machine learning model to automate data preparation for CFD simulations. You will collaborate with engineers, conduct literature reviews, and create training datasets.
Job Technologies
Your role in the team
Location: Graz / asap / duration 6 months
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 accelerate the data preparation process for comprehensive 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 the previously created dataset. Optimize the model setup if necessary.
- Create documentation and propose additional work to speed-up data preparation.
This text has been machine translated. Show original
Our expectations of you
Education
- Ongoing technical study at the university / university of applied sciences in mechanical engineering, automotive engineering, computer science or similar.
Qualifications
- A good understanding of Python coding and machine learning libraries (e.g., PyTorch, NumPy, TensorFlow) is essential.
- Basics in Beta CAE Systems software package ANSA are advantageous but not necessary.
- Strong interest in bringing state-of-the-art machine learning to real-world industry applications.
- High level of helpfulness and excellent communication skills.
Experience
- Basic knowledge and experience in the field of numerics and CFD are beneficial but not mandatory.
This text has been machine translated. Show original
Benefits
Work-Life-Integration
- 🧳Relocation Support
- 🕺No Dresscode
- ⏸Educational Leave/Sabbatical
- 🏝Extra Holidays
- 🚌Excellent Traffic Connections
- 🏠Home Office
- 🍼Day Care for Kids
- 🅿️Employee Parking Space
- ⏰Flexible Working Hours
Health, Fitness & Fun
- 🧠Mental Health Care
- 🚲Bicycle Parking Space
- 🏋🏿♂️Fitness Offers
- 👩⚕️Company Doctor
- 🙂Health Care Benefits
- 🎳Team Events
- 👨🏻🎓Mentor Program
- ♿️No Physical Barriers
Food & Drink
More net
Job Locations
Topics that you deal with on the job
This is your employer
Magna
Graz, Klagenfurt, Lannach, Weiz, Weikersdorf Am Steinfelde, Traiskirchen, Sankt Valentin, Wien, München, Mühlhausen Im Täle, Sindelfingen, Ingolstadt, Leonberg, Sailauf, Schleiz, Köln, Heilbad Heiligenstadt, Wolfsburg
Magna is a leading technology and mobility company, with 344 production plants and 93 product development, engineering, and sales centers in 27 countries. As the largest automotive supplier in the world, Magna is helping to shape the biggest transformation in auto history by leading the way in electric vehicles, autonomous driving, and innovative manufacturing processes. We offer you all of the opportunity to help create the next generation of cars – join us as we shape the future of mobility together!
Description
- Company Size
- 250+ Employees
- Founding year
- 1957
- Language
- German, English
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Vehicle Manufacturing, Supplier, Electronics, Automatization, Internet, IT, Telecommunication
Dev Reviews
by devworkplaces.com
Total
(3 Reviews)Career Growth
4.1Workingconditions
4.2Engineering
3.5Culture
4.3