Re­se­arch Po­si­ti­on

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 investigate multimodal robot perception across complementary sensor modalities (e. g. RGB cameras, depth cameras, LiDAR, ultrasonic sensors, laser scanners) (20 %) focus on bidirectional sim-to-real and real-to-sim integration with dynamic digital twins (20 %) use the resulting perception stack as a key component in robot-learning based on deep reinforcement learning (15 %) publishing on highly ranked international conferences and high-impact journals (15 %) presenting results to a broader audience, SMEs, and the scientific community (10 %) participate in industrial projects (20 %) Employment is conducive to scientific qualification and provides the opportunity for further academic development. We offer salary according to Remuneration level 13 TV-L 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) fulltime internal and external training opportunities amount of health, consulting and prevention services reconcilability of family and working life constant place of work (Bielefeld) without travel activities flexible working hours supplementary company pension Your Profile We expect completed scientific academic degree (e. g. Master's degree or equivalent) in a technical field of study programming skills in Python robotics knowledge knowledge of image processing knowledge of AI/ML cooperative and team-oriented approach to working independent, self-reliant and committed style of work ability to present results interest in interdisciplinary scientific collaboration very good written and spoken English skills  Preferred experience and skills knowledge of simulations (e. g. MuJoCo, IsaacSim) 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