Re­se­arch Po­si­ti­on

CAVECORE (Continuous, Automated Validation, and Evaluation of Cognitive Robots in Open-Ended Environments) is a Marie Sklodowska-Curie Doctoral Network that trains the next generation of researchers to advance cognitive robotics—robots that can interact, learn, and adapt in open-ended real-world environments. The network addresses one of the central challenges in AI-enabled robotics: evaluating and validating the quality, safety, and reliability of such robots in a systematic and trustworthy manner. In addition, 2 secondments in CAVECORE partner institutions are planned. The specific doctoral topic DC5 is named “Reliable Integration of Safety-Constraints into the Learning Process of Collaborative Robots”. The goal is to integrate Reinforcement Learning and Imitation Learning approaches for acquiring complex robotic manipulation skills in collaborative settings while ensuring compliance with functional safety regulations. Please note that, in accordance with the requirements of the third-party funding provider, only applicants who have spent a maximum of 12 months in Germany during the past three years can be considered. Your Tasks studying safe and reliable AI-robotics systems (20 %) development of a framework that integrates reinforcement learning and imitation learning approaches for acquiring complex robotic manipulation skills (20 %) ensuring compliance with functional safety regulations, e. g. collision avoidance (15 %) incorporating validity concepts for machine learning methods and utilize safety techniques such as shielding to meet safety-critical requirements (15 %) integration of a fast, reactive digital twin (DT), leveraging co-simulation to anticipate and prevent unsafe scenarios in real-time (15 %) enabling proactive behavioral adjustments and sim-to-real skill development (10 %) publishing results in scientific conferences and journals (5 %) Employment is conducive to scientific qualification and provides the opportunity for further academic development. Your Profile We expect completed scientific academic degreein a technical field of study programming skills in Python robotics knowledge knowledge of AI/ML pursuit of a doctorate cooperative and team-oriented approach to work independent, self-reliant and committed approach to work ability to present results Preferred experience and skills knowledge of simulations (e. g. MuJoCo, IsaacSim) knowledge of functional safety knowledge of image processing 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 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