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Master Thesis: Machine Learning (ML)-Based Methods as Surrogate for Finite Element Modelling(m/w/x)
Developing and validating surrogate models for engineering simulations, including dataset creation and model implementation. Good Python experience and basic machine learning knowledge required. Access to state-of-the-art machine park.
Anforderungen
- Studying mechanical engineering or similar
- Good experience in Python
- Basic knowledge of machine learning
- Good language skills in German and/or English
Aufgaben
- Investigate ML methods for FEM surrogates.
- Create and prepare datasets for use cases.
- Implement selected ML model and validate results.
- Document and prepare results.
Ausbildung
- Laufendes Studium
Sprachen
- Deutsch – verhandlungssicher
- Englisch – verhandlungssicher
Tools & Technologien
- Python
Benefits
Mentoring & Coaching
- Professional supervision and collaboration
Startup-Atmosphäre
- Early team integration and responsibility
Moderne Technikausstattung
- State-of-the-art machine park
Noch nicht perfekt?
- Fraunhofer-GesellschaftVollzeitPraktikumnur vor OrtAachen
- Fraunhofer-Gesellschaft
Master Thesis: An Industry 4.0-oriented approach to automated simulation-based process optimization(m/w/x)
Vollzeit/TeilzeitPraktikumnur vor OrtAachen - Fraunhofer-Gesellschaft
Master Thesis: Automated Process Optimization through Industry 4.0 Simulation(m/w/x)
VollzeitWerkstudentnur vor OrtAachen - Fraunhofer-Gesellschaft
BT/MT: Deep learning and machine learning in production(m/w/x)
VollzeitWerkstudentnur vor OrtAachen - Fraunhofer-Gesellschaft
Bachelor-/ Master Thesis: Investigation of effects of surface metrology data on optical simulation(m/w/x)
VollzeitWerkstudentnur vor OrtAachen
Master Thesis: Machine Learning (ML)-Based Methods as Surrogate for Finite Element Modelling(m/w/x)
Developing and validating surrogate models for engineering simulations, including dataset creation and model implementation. Good Python experience and basic machine learning knowledge required. Access to state-of-the-art machine park.
Anforderungen
- Studying mechanical engineering or similar
- Good experience in Python
- Basic knowledge of machine learning
- Good language skills in German and/or English
Aufgaben
- Investigate ML methods for FEM surrogates.
- Create and prepare datasets for use cases.
- Implement selected ML model and validate results.
- Document and prepare results.
Ausbildung
- Laufendes Studium
Sprachen
- Deutsch – verhandlungssicher
- Englisch – verhandlungssicher
Tools & Technologien
- Python
Benefits
Mentoring & Coaching
- Professional supervision and collaboration
Startup-Atmosphäre
- Early team integration and responsibility
Moderne Technikausstattung
- State-of-the-art machine park
Über das Unternehmen
Fraunhofer-Gesellschaft
Branche
Research
Beschreibung
The Fraunhofer-Gesellschaft operates 76 institutes and research units throughout Germany and is a leading applied research organization. It focuses on developing key technologies and enabling commercial utilization by business and industry.
Noch nicht perfekt?
- Fraunhofer-Gesellschaft
Masterarbeit: ML-basierte Methoden als Ersatz für die Finite-Elemente-Modellierung(m/w/x)
VollzeitPraktikumnur vor OrtAachen - Fraunhofer-Gesellschaft
Master Thesis: An Industry 4.0-oriented approach to automated simulation-based process optimization(m/w/x)
Vollzeit/TeilzeitPraktikumnur vor OrtAachen - Fraunhofer-Gesellschaft
Master Thesis: Automated Process Optimization through Industry 4.0 Simulation(m/w/x)
VollzeitWerkstudentnur vor OrtAachen - Fraunhofer-Gesellschaft
BT/MT: Deep learning and machine learning in production(m/w/x)
VollzeitWerkstudentnur vor OrtAachen - Fraunhofer-Gesellschaft
Bachelor-/ Master Thesis: Investigation of effects of surface metrology data on optical simulation(m/w/x)
VollzeitWerkstudentnur vor OrtAachen