Die KI-Suchmaschine für Jobs
Thesis in Development of a Learning Based Compositional Electrical Drive Model(m/w/x)
Beschreibung
In this role, you will dive into the world of electric drives, conducting research and developing dynamic models. Your work will focus on creating a compositional model that integrates physical and data-based approaches, ultimately optimizing performance through innovative techniques.
Lass KI die perfekten Jobs für dich finden!
Lade deinen CV hoch und die Nejo-KI findet passende Stellenangebote für dich.
Anforderungen
- •Studies in Electrical Engineering, Cybernetics, Physics, Computer Science, or comparable
- •Experience in Machine Learning and Python; modelling of dynamical systems
- •Flexibility, enthusiasm, and responsibility
- •Good in German and English
- •Enrollment at university
Ausbildung
Aufgaben
- •Familiarize yourself with physical models of electric drives
- •Conduct literature research on existing ML-based approaches for electric drive identification
- •Develop a dynamic physical electrical drive model combined with data-based models
- •Implement a proof of concept to demonstrate gradient-based optimization of the overall model using dynamical data with ODE solvers
Sprachen
Deutsch – verhandlungssicher
Englisch – verhandlungssicher
- Bosch GroupVollzeitPraktikumnur vor OrtRenningen
- Bosch Group
Master Thesis in Validation and Optimization of Controllers Using Foundation Models(m/w/x)
Vollzeitnur vor OrtKeine AngabeRenningen - Fraunhofer-Gesellschaft
Master Thesis - Reinforcement Learning for wheeled, bipedal robots(m/w/x)
VollzeitPraktikumnur vor OrtStuttgart - Bosch Group
Master Thesis Automated Scalable Deployment of Predictive Maintenance in Cloud(m/w/x)
VollzeitPraktikumnur vor OrtStuttgart - Fraunhofer-Gesellschaft
Masterthesis - Model Predictive Path Following with System Identification and Wheel Slip Estimation(m/w/x)
VollzeitPraktikumnur vor OrtStuttgart
Thesis in Development of a Learning Based Compositional Electrical Drive Model(m/w/x)
Die KI-Suchmaschine für Jobs
Beschreibung
In this role, you will dive into the world of electric drives, conducting research and developing dynamic models. Your work will focus on creating a compositional model that integrates physical and data-based approaches, ultimately optimizing performance through innovative techniques.
Lass KI die perfekten Jobs für dich finden!
Lade deinen CV hoch und die Nejo-KI findet passende Stellenangebote für dich.
Anforderungen
- •Studies in Electrical Engineering, Cybernetics, Physics, Computer Science, or comparable
- •Experience in Machine Learning and Python; modelling of dynamical systems
- •Flexibility, enthusiasm, and responsibility
- •Good in German and English
- •Enrollment at university
Ausbildung
Aufgaben
- •Familiarize yourself with physical models of electric drives
- •Conduct literature research on existing ML-based approaches for electric drive identification
- •Develop a dynamic physical electrical drive model combined with data-based models
- •Implement a proof of concept to demonstrate gradient-based optimization of the overall model using dynamical data with ODE solvers
Sprachen
Deutsch – verhandlungssicher
Englisch – verhandlungssicher
Über das Unternehmen
Bosch Group
Branche
Engineering
Beschreibung
Das Unternehmen entwickelt hochwertige Technologien und Dienstleistungen, die das Leben der Menschen verbessern.
- Bosch Group
Masterarbeit im Bereich adaptiver Regelung von elektrischen Antrieben(m/w/x)
VollzeitPraktikumnur vor OrtRenningen - Bosch Group
Master Thesis in Validation and Optimization of Controllers Using Foundation Models(m/w/x)
Vollzeitnur vor OrtKeine AngabeRenningen - Fraunhofer-Gesellschaft
Master Thesis - Reinforcement Learning for wheeled, bipedal robots(m/w/x)
VollzeitPraktikumnur vor OrtStuttgart - Bosch Group
Master Thesis Automated Scalable Deployment of Predictive Maintenance in Cloud(m/w/x)
VollzeitPraktikumnur vor OrtStuttgart - Fraunhofer-Gesellschaft
Masterthesis - Model Predictive Path Following with System Identification and Wheel Slip Estimation(m/w/x)
VollzeitPraktikumnur vor OrtStuttgart