Research Postion (m/f/d) - Doctoral Network CAVECORE, Dr.-Ing. Sebastian Wrede
CAVECORE (Continuous, Automated Validation, and Evaluation of Cognitive Robots in Open-Ended Environments) is a Marie-Sklodowska-Curie-Actions (MSCA) 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 doctoral project DC10 within the CAVECORE MSCA project tackles the challenge of achieving predictable, transparent, and verifiably safe autonomy in human–robot collaboration by developing a new scenario-based specification and validation methodology. Domain-specific models with concepts and metrics for human-robot collaboration encoded in knowledge graphs shall provide the semantic structure needed to express acceptance criteria that remain meaningful even when robots use learned or foundation-model–based strategies. A digital-twin–based validation environment – implemented, for example, in NVIDIA Omniverse – will enable real-time measurement and automated testing of robotic and human agents in collaborative scenarios, effectively facilitating a highly automated specification–validation loop for AI-based robot systems.
The PhD project will be jointly supervised by Dr.-Ing. Sebastian Wrede from the Technical Faculty of Bielefeld University and Prof. Dr. Nico Hochgeschwender from the University of Bremen.
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.
- conduct research on explainable, transparent, and reliable autonomy for collaborative robotic systems (30 %)
- model domain-specific concepts and acceptance criteria for specification of complex human–robot interaction scenarios using knowledge graphs (15 %)
- develop mechanisms for semantic traceability between specifications, observed behavior, and AI-driven decisions (15 %)
- analyze and assess the transferability of simulation-based validation results to real-world collaborative robotic scenarios (15 %)
- disseminate research findings through scientific publications, presentations, and contributions to the advancement of the field (15 %)
- build a digital-twin environment for automated validation - e.g., in NVIDIA Omniverse - including the design of appropriate measurement and monitoring models (10 %)
Employment is conducive to scientific qualification and provides the opportunity for further academic development.
- salary according to Remuneration level TV-L E13
- 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 the contract may differ in individual cases)
- fulltime
- internal and external training opportunities
- variety of health, consulting and prevention services
- reconcilability of family and work
- flexible working hours
- supplementary company pension
- completed scientific academic degree in a technical field of study
- solid programming skills in Python, C++ or Rust
- experience in robotics and simulation or software engineering, in particular formal specification, model-based development, automated testing
- interest in AI/ML, explainable autonomy, and human–robot collaboration
- motivation to pursue a doctorate in an interdisciplinary research context
- cooperative and team-oriented working style
- independent, reliable, and committed approach to scientific work
- ability to clearly communicate and present research results
- knowledge of functional safety and risk assessment
- familiarity with relevant norms and ISO specifications, e. g., ISO10218-2:2025
- experience in scenario-based approaches such as OpenSCENARIO2
We are looking forward to receiving your application. To apply, please preferably use our online form via the application button below.
application deadline: 05.03.2026