Research Associate in Reinforcement Learning for Planning Problems | Wissenschaftliche/r Mitarbeiter/in Bereich Reinforcement Learning für Planungsprobleme (25321)

Job Summary

This role involves cutting-edge scientific research and development in Artificial Intelligence, focusing specifically on Reinforcement Learning (RL) and Deep Learning (DL) methods to solve complex industrial planning problems, such as aircraft fuselage production and assembly. The Research Associate will be responsible for scientifically exploring new approaches in Neural Combinatorial Optimization, training and evaluating learning models, and publishing results in prestigious scientific journals and conferences. This is a full-time, fixed-term position within an interdisciplinary research team at the University of Wuppertal, offering the opportunity for further scientific qualification and collaboration with industry partners. Candidates must possess a Master's degree in a relevant technical field, strong interest in applied AI research, excellent communication skills, and fluency in German, alongside very good English skills. Experience with a programming language (like Python or Java) and familiarity with DL/RL frameworks (TensorFlow, PyTorch) are essential for success in this demanding research environment.