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Internship/ Master Thesis - Machine Learning and Control Systems(m/w/x)
Developing digital twins for dynamic adaptation of industrial machines using AI in control systems. Proficiency in Python and ML frameworks required. Flexible working hours, attractive remuneration.
Anforderungen
- Master student in mechatronics, electrical engineering, mechanical engineering or similar
- Proficiency in Python and machine learning frameworks (TensorFlow, PyTorch)
- Knowledge of PLCs and control systems
- Strong statistics fundamentals
- Basic understanding of reinforcement learning
- Teamwork, creativity, and interest in innovative technical solutions
- Strong communication skills and structured work approach
- Study regulations with required duration (for mandatory internships)
- Current certificate of enrolment
- Current transcript of records
- Valid residence permit
- Work permit including supplementary sheet
Aufgaben
- Contribute to real-world industrial challenges
- Optimize machines through data-driven solutions
- Collaborate with an innovative team
- Explore AI methodologies in control systems
- Develop digital twins for dynamic adaptation
- Experiment with time-series and tabular machine learning models
- Apply signal processing techniques
- Improve model performance through feature engineering
- Develop adaptive control systems
- Deploy models in production environments
- Industrialize machine learning models
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
- Deutsch – verhandlungssicher
Tools & Technologien
- Python
- TensorFlow
- PyTorch
- PLCs
- control systems
Benefits
Flexibles Arbeiten
- Flexible working hours
Attraktive Vergütung
- Attractive remuneration
Lockere Unternehmenskultur
- International and dynamic work environment
Sonstige Vorteile
- Qualified support from specialists
- Diversity and Inclusion
Gesundheits- & Fitnessangebote
- Health-oriented workplace
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Internship/ Master Thesis - Machine Learning and Control Systems(m/w/x)
Developing digital twins for dynamic adaptation of industrial machines using AI in control systems. Proficiency in Python and ML frameworks required. Flexible working hours, attractive remuneration.
Anforderungen
- Master student in mechatronics, electrical engineering, mechanical engineering or similar
- Proficiency in Python and machine learning frameworks (TensorFlow, PyTorch)
- Knowledge of PLCs and control systems
- Strong statistics fundamentals
- Basic understanding of reinforcement learning
- Teamwork, creativity, and interest in innovative technical solutions
- Strong communication skills and structured work approach
- Study regulations with required duration (for mandatory internships)
- Current certificate of enrolment
- Current transcript of records
- Valid residence permit
- Work permit including supplementary sheet
Aufgaben
- Contribute to real-world industrial challenges
- Optimize machines through data-driven solutions
- Collaborate with an innovative team
- Explore AI methodologies in control systems
- Develop digital twins for dynamic adaptation
- Experiment with time-series and tabular machine learning models
- Apply signal processing techniques
- Improve model performance through feature engineering
- Develop adaptive control systems
- Deploy models in production environments
- Industrialize machine learning models
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
- Deutsch – verhandlungssicher
Tools & Technologien
- Python
- TensorFlow
- PyTorch
- PLCs
- control systems
Benefits
Flexibles Arbeiten
- Flexible working hours
Attraktive Vergütung
- Attractive remuneration
Lockere Unternehmenskultur
- International and dynamic work environment
Sonstige Vorteile
- Qualified support from specialists
- Diversity and Inclusion
Gesundheits- & Fitnessangebote
- Health-oriented workplace
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Continental
Branche
Manufacturing
Beschreibung
Das Unternehmen ist eine Tochterfirma der Continental AG und gehört zu einem der führenden Industriespezialisten weltweit.
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