Thesis Work for Offline Reinforcement Learning with Physics-Informed Data-Driven Models
Career(1 month ago)
About this role
A Master's thesis position at ABB Research in Västerås focused on model-based offline reinforcement learning for industrial control. The work explores combining physics knowledge and data to refine physics-based simulators using Physics-Informed Machine Learning and hybrid modeling. The 5-month placement is part of ABB's talent pipeline for future opportunities.
Required Skills
- Reinforcement Learning
- Physics-Informed ML
- System Identification
- Control Systems
- Simulation
- Python
- Data Analysis
- Research
Qualifications
- Master's Student in Computer Science
- Master's Student in Industrial Engineering
- Master's Student in Related Field
About Career
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