Master s Thesis „Machine Learning Models for Data Preparation in Automotive CFD-Simulation Process“
Master s Thesis „Machine Learning Models for Data Preparation in Automotive CFD-Simulation Process“
Master s Thesis „Machine Learning Models for Data Preparation in Automotive CFD-Simulation Process“
Master s Thesis „Machine Learning Models for Data Preparation in Automotive CFD-Simulation Process“
Magna
Automobil- und Fahrzeugbau
Graz
- Art der Anstellung: Teilzeit
- Vor Ort
- Zu den Ersten gehören
Master s Thesis „Machine Learning Models for Data Preparation in Automotive CFD-Simulation Process“
Über diesen Job
Master's Thesis "Machine Learning Models for Data Preparation in Automotive CFD-Simulation Process"
- locations
- Graz, AT
- time type
- Part time
- posted on
- Posted Today
- job requisition id
- R00212032
Job descriptions may display in multiple languages based on your language selection.
What we offer:
Group Summary:
Job Responsibilities:
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 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.
Who we are looking for
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.
Site Benefits
Mobility offers and parking spaces - Arriving at work is easy!
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.
And now: It’s your turn!
We are looking forward to receiving your application. Please include your CV. As we are excited to learn more about you, please also submit a covering letter.
If you have any questions, please don’t hesitate to contact us
Katrin Prager, MSc (WU)
+43 664 8840 2839
Magna Steyr Fahrzeugtechnik GmbH & Co KG
Awareness, Unity, Empowerment:
Bewertung von Mitarbeitenden
Gesamtbewertung
Basierend auf 1.632 BewertungenVorteile für Mitarbeitende
Unternehmenskultur
Unternehmenskultur
1632 Mitarbeitende haben abgestimmt: Sie bewerten die Unternehmenskultur bei Magna als ausgeglichen zwischen traditionell und modern.Dies stimmt ungefähr mit dem Branchen-Durchschnitt überein.