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

Job Summary

This role is a stimulating opportunity for a dedicated Research Associate to join the Institute for Technologies and Management of Digital Transformation at the University of Wuppertal. Focusing on the 'Industrial Deep Learning' research area, the associate will primarily contribute to the Flex4Green project, developing innovative Reinforcement Learning and Deep Learning methods specifically for complex industrial planning and assembly problems, such as those found in aircraft fuselage production. Day-to-day tasks involve the scientific exploration of Neural Combinatorial Optimization, model development, training, and evaluation, alongside publishing and presenting research findings at conferences and in journals. The ideal candidate holds a Master's degree in Computer Science, Mathematics, or a related engineering field, possesses strong interest in applied AI research, and has practical experience with programming and Deep Learning/RL frameworks like TensorFlow or PyTorch. This is a full-time, fixed-term position (until 30.06.2027) offering significant academic qualification opportunities and collaboration within an interdisciplinary team.