Ruhr-Universität Bochum
44801 Bochum - Deutschland
Informatiker/in
Arbeit
Vollzeit
ab 18.12.2025
Beschreibung
**In order to fill a fixed-term position in full-time (39.8300 hours/week = 100%) starting on the earliest date possible, we are looking for a**
### Full-time PhD researcher (m,f,x) on Artificial Intelligence and Formal Methods, for three years
The chair of Artificial Intelligence and Formal Methods at the Ruhr-University Bochum in Germany (headed by Prof. Dr. Nils Jansen) has a mission: Increasing the trustworthiness of Artificial Intelligence (AI). We conduct broad foundational and application-driven research on neurosymbolic AI. The following goals are central to our efforts: 1. Increase the dependability of AI in safety-critical environments. 2. Render AI models robust against uncertain knowledge about their environment. 3. Enhance the capabilities of formal verification to handle real-world problems using learning techniques. We are interested in various aspects of dependability and safety in AI, intelligent decision-making under uncertainty, and safe reinforcement Learning. A key aspect of our research is a thorough understanding of the (epistemic or aleatoric) uncertainty that may occur when AI systems operate in the real world. We publish regularly in the top venues and journals of Artificial Intelligence (AAAI, IJCAI, ICLR, NeurIPS, JAIR), Formal Methods (CAV, TACAS), and Control Theory (Transactions on Automatic Control). You can find our latest results at https://ai-fm.org/publications/.
The research of this position aims broadly at the intersection of formal verification and machine learning. In particular, the aim is to address major challenges in ensuring the safety of reinforcement learning methods: Complex environments with large degrees of freedom and high-dimensional feature spaces, realistic, continuous spaces, and the inherent uncertainty that reinforcement learning agents face in the real world. The project proposes interdisciplinary approaches from the intersection of Machine Learning, Artificial Intelligence, Formal Methods, Robotics, and Control Theory. Many variations or further topics within the group’s broad research scheme are possible.
Scope: full-time
Duration: fixed-term, 3 years
Start: starting on the earliest date possible
Apply by: 2026-01-05
**Your tasks:**
- The main task of this position is to conduct research in the broad research area of the chair of Artificial Intelligence and Formal Methods.
- There will be freedom to shape the chair in an excellent research environment in close collaboration with Radboud University, Nijmegen, RWTH Aachen University, The University of Oxford, and The University of Texas at Austin.
- Support of the chair’s teaching program in the form of conducting exercises and the organization of seminars and practical courses (esp. in the areas of artificial intelligence, formal verification, and programming languages).
**Your profile:**
- Master’s degree in Computer Science, Electrical Engineering, or related fields.
- Excellent interpersonal and communication skills in English.
- Background in one or more of the following areas is beneficial, but not necessary: Formal Methods, Artificial Intelligence, Machine Learning, Control Theory, and Robotics.
- Experience in software development including experience with programming languages, such as Python, Java, or C/C++ is a plus.
[https://jobs.ruhr-uni-bochum.de/jobposting/bdff0ae061efdec9655491d5b968169aebd8f2e00?ref=AfA](https://jobs.ruhr-uni-bochum.de/jobposting/bdff0ae061efdec9655491d5b968169aebd8f2e00?ref=AfA)
### Full-time PhD researcher (m,f,x) on Artificial Intelligence and Formal Methods, for three years
The chair of Artificial Intelligence and Formal Methods at the Ruhr-University Bochum in Germany (headed by Prof. Dr. Nils Jansen) has a mission: Increasing the trustworthiness of Artificial Intelligence (AI). We conduct broad foundational and application-driven research on neurosymbolic AI. The following goals are central to our efforts: 1. Increase the dependability of AI in safety-critical environments. 2. Render AI models robust against uncertain knowledge about their environment. 3. Enhance the capabilities of formal verification to handle real-world problems using learning techniques. We are interested in various aspects of dependability and safety in AI, intelligent decision-making under uncertainty, and safe reinforcement Learning. A key aspect of our research is a thorough understanding of the (epistemic or aleatoric) uncertainty that may occur when AI systems operate in the real world. We publish regularly in the top venues and journals of Artificial Intelligence (AAAI, IJCAI, ICLR, NeurIPS, JAIR), Formal Methods (CAV, TACAS), and Control Theory (Transactions on Automatic Control). You can find our latest results at https://ai-fm.org/publications/.
The research of this position aims broadly at the intersection of formal verification and machine learning. In particular, the aim is to address major challenges in ensuring the safety of reinforcement learning methods: Complex environments with large degrees of freedom and high-dimensional feature spaces, realistic, continuous spaces, and the inherent uncertainty that reinforcement learning agents face in the real world. The project proposes interdisciplinary approaches from the intersection of Machine Learning, Artificial Intelligence, Formal Methods, Robotics, and Control Theory. Many variations or further topics within the group’s broad research scheme are possible.
Scope: full-time
Duration: fixed-term, 3 years
Start: starting on the earliest date possible
Apply by: 2026-01-05
**Your tasks:**
- The main task of this position is to conduct research in the broad research area of the chair of Artificial Intelligence and Formal Methods.
- There will be freedom to shape the chair in an excellent research environment in close collaboration with Radboud University, Nijmegen, RWTH Aachen University, The University of Oxford, and The University of Texas at Austin.
- Support of the chair’s teaching program in the form of conducting exercises and the organization of seminars and practical courses (esp. in the areas of artificial intelligence, formal verification, and programming languages).
**Your profile:**
- Master’s degree in Computer Science, Electrical Engineering, or related fields.
- Excellent interpersonal and communication skills in English.
- Background in one or more of the following areas is beneficial, but not necessary: Formal Methods, Artificial Intelligence, Machine Learning, Control Theory, and Robotics.
- Experience in software development including experience with programming languages, such as Python, Java, or C/C++ is a plus.
[https://jobs.ruhr-uni-bochum.de/jobposting/bdff0ae061efdec9655491d5b968169aebd8f2e00?ref=AfA](https://jobs.ruhr-uni-bochum.de/jobposting/bdff0ae061efdec9655491d5b968169aebd8f2e00?ref=AfA)
Quelle: Bundesagentur für Arbeit - Rechtliche Hinweise zur Nutzung
Ob die Stelle noch verfügbar ist und weitere Informationen findest du direkt auf der Website der Bundesagentur für Arbeit. Bitte beachte: OPROMA ist nicht der Anbieter dieser Stelle und kann keine Auskünfte geben.
Ob die Stelle noch verfügbar ist und weitere Informationen findest du direkt auf der Website der Bundesagentur für Arbeit. Bitte beachte: OPROMA ist nicht der Anbieter dieser Stelle und kann keine Auskünfte geben.
Ref-Nr.: 395ee2bad6ac76630634cb35c00582d8
Letztes Update:
19.12.2025
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