AI-powered robotics is rapidly advancing and increasingly helping small and medium-sized enterprises (SMEs) deploy highly flexible automation in challenging settings such as high-mix, low-volume production. Perception of cluttered, dynamic environments remains difficult, but recent progress in foundation models operating on camera, depth cameras, and LiDAR data is making it more and more feasible. Combined with large language models (LLMs), robots are beginning to exhibit elements of grounded common-sense reasoning and task planning. The goal of this PhD project is to develop and rigorously evaluate new perception capabilities for AI-powered robotics operating with deep reinforcement learning (DRL) capabilities in industrial automation. Your Tasks
1. investigate multimodal robot perception across complementary sensor modalities (e. g. RGB cameras, depth cameras, LiDAR, ultrasonic sensors, laser scanners) (20 %)
2. focus on bidirectional sim-to-real and real-to-sim integration with dynamic digital twins (20 %)
3. use the resulting perception stack as a key component in robot-learning based on deep reinforcement learning (15 %)
4. publishing on highly ranked international conferences and high-impact journals (15 %)
5. presenting results to a broader audience, SMEs, and the scientific community (10 %)
6. participate in industrial projects (20 %)
Employment is conducive to scientific qualification and provides the opportunity for further academic development. We offer
7. salary according to Remuneration level 13 TV-L
8. fixed-term (3 years) (§ 2 (1) sentence 1 of the WissZeitVG; in accordance with the provisions of the WissZeitVG and the Agreement on Satisfactory Conditions of Employment, the length of contract may differ in individual cases)
9. fulltime
10. internal and external training opportunities
11. amount of health, consulting and prevention services
12. reconcilability of family and working life
13. constant place of work (Bielefeld) without travel activities
14. flexible working hours
15. supplementary company pension
Your Profile We expect
16. completed scientific academic degree (e. g. Master's degree or equivalent) in a technical field of study
17. programming skills in Python
18. robotics knowledge
19. knowledge of image processing
20. knowledge of AI/ML
21. cooperative and team-oriented approach to working
22. independent, self-reliant and committed style of work
23. ability to present results
24. interest in interdisciplinary scientific collaboration
25. very good written and spoken English skills
Preferred experience and skills
26. knowledge of simulations (e. g. MuJoCo, IsaacSim)
27. knowledge of large language models
Application Procedure
We are looking forward to receiving your application. To apply, please preferably use our online form via the application button below.
application deadline: Contact
Prof. Dr. rer. nat. Klaus Neumann
+49 521 106-67750
Postal Address
Universität Bielefeld
Faculty of Technology
Prof. Dr. rer. nat. Klaus Neumann
Postfach 10 01 31
33501 Bielefeld