Masterand (d/m/w) im Bereich Deep Reinforcement Learning für die Luftfahrtproduktion
Core
Designing and implementing a Deep Reinforcement Learning framework to optimize production planning and resource utilization for helicopter assembly.
Role type
Master's thesis student in Deep Reinforcement Learning
Builds
RL frameworks for production planning optimization
Domain
Aerospace manufacturing / Industrial AI
Deliverable
production ML models
Required skills
Deep Reinforcement Learning, Python, ML Frameworks, Large Data Processing
Preferred skills
Palantir Skywise experience
Technologies
Python, Palantir Skywise
Responsibilities
Define RL agent, model environments, and design reward functions; Select and implement DRL algorithms; Define KPIs for production planning and visualize training processes; Develop implementation strategy for shopfloor deployment.
Sourced via adzuna · Listed on CareerPlan, which tracks 70,000+ jobs from 20+ sources.
