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Master Thesis - Imitation and Transfer Learning of Model Predictive Controllers(m/w/x)
Developing learning-based controllers for optimal control systems. Model predictive control algorithm experience required. Student events, personal HR contact.
Requirements
- Bachelor’s degree in Control Engineering, Automation Engineering, Systems Engineering or similar
- Solid theoretical foundations on control theory
- First experience with model identification and data analysis
- Ability to build and run optimal control algorithms
- Ability to build and run model predictive control algorithms
- First experience with programming languages (e.g., Python, C/C++)
- Sound English skills in speaking and writing
- Experience in numerical optimization (advantageous)
- Experience in use of different optimization solvers (e.g., Ipopt, Gurobi, Cplex) (advantageous)
- Master’s thesis completion with four months on-site
Tasks
- Contribute to ongoing research on learning-based optimal control
- Develop control strategies using imitation learning and surrogate models
- Explore various architectures and algorithms for learning-based controllers
- Evaluate performance of learning-based and imitation-based controllers
- Gain practical experience in a project team
- Work independently on assigned tasks
- Collaborate with competent experts and gain technology insights
- Get familiar with new and complex topics
- Participate in code development
Education
- Currently in higher educationOR
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- C/C++
- Ipopt
- Gurobi
- Cplex
Benefits
Team Events
- Student events
Informal Culture
- Personal contact with HR
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Master Thesis - Imitation and Transfer Learning of Model Predictive Controllers(m/w/x)
Developing learning-based controllers for optimal control systems. Model predictive control algorithm experience required. Student events, personal HR contact.
Requirements
- Bachelor’s degree in Control Engineering, Automation Engineering, Systems Engineering or similar
- Solid theoretical foundations on control theory
- First experience with model identification and data analysis
- Ability to build and run optimal control algorithms
- Ability to build and run model predictive control algorithms
- First experience with programming languages (e.g., Python, C/C++)
- Sound English skills in speaking and writing
- Experience in numerical optimization (advantageous)
- Experience in use of different optimization solvers (e.g., Ipopt, Gurobi, Cplex) (advantageous)
- Master’s thesis completion with four months on-site
Tasks
- Contribute to ongoing research on learning-based optimal control
- Develop control strategies using imitation learning and surrogate models
- Explore various architectures and algorithms for learning-based controllers
- Evaluate performance of learning-based and imitation-based controllers
- Gain practical experience in a project team
- Work independently on assigned tasks
- Collaborate with competent experts and gain technology insights
- Get familiar with new and complex topics
- Participate in code development
Education
- Currently in higher educationOR
- Bachelor's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- C/C++
- Ipopt
- Gurobi
- Cplex
Benefits
Team Events
- Student events
Informal Culture
- Personal contact with HR
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
ABB AG
Industry
EnergyAutomation
Description
Das Unternehmen ist ein globaler Marktführer, der Industrien dabei unterstützt, effizienter und umweltfreundlicher zu arbeiten.
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