项目介绍

2026年3月30日

Project and Job Description 

We invite applications for a fully funded PhD position in the area of safe data-driven system identification for cyber-physical systems, offered by our research group at the intersection of control theory, machine learning, and formal methods. The successful candidate will contribute to advancing data-driven modeling techniques that enable formal safety guarantees for complex dynamical systems such as autonomous vehicles, robotics, and industrial systems. Building on recent work in reachset-conformant identification, the project focuses on constructing abstractions whose reachable sets provably overapproximate all observable system behaviors, thereby enabling the sound transfer of safety properties from models to real-world systems. The research combines methodological innovation with real-world impact and includes topics such as scalable identification algorithms, uncertainty quantification, and the integration of learning-based models with formal verification. We offer a supportive, inclusive, and collaborative research environment that actively encourages diversity of perspectives and backgrounds, and we particularly welcome applications from women and underrepresented groups in engineering and computer science.

The position is embedded in an internationally visible research group with strong ties to leading academic institutions and industry partners, providing excellent opportunities for interdisciplinary collaboration, conference participation, and research stays abroad. The PhD candidate will benefit from structured supervision, mentoring, and a collegial team culture that values mutual support, work-life balance, and personal development. We are committed to fostering an environment in which all researchers can thrive, contribute their ideas, and grow into independent scientists. The position is fully funded, with a competitive salary and access to state-of-the-art research infrastructure. Applications will be reviewed on a rolling basis until the position is filled.

Previous Work

https://ieeexplore.ieee.org/document/11250664

https://www.jmlr.org/papers/v26/25-1161.html

Job Specifications

• For PhD applicants: Excellent Master’s degree (or equivalent) in engineering, computer science, or related disciplines (typically mathematics, physics).
• For Postdoc applicants: Excellent track record in engineering or computer science.
• Fluency in spoken and written English is required.
• Proficient in at least one programming language, e.g. MATLAB, C/C++, Python.
• Highly motivated and keen on working in an international and interdisciplinary team.
• Applicants with strong background in the following fields are preferred:
  • Dynamical Systems
  • Formal Methods
  • Reachability Analysis
  • Computational Geometry

Context

The applicant will be directly advised by Prof. Matthias Althoff ( https://www.ce.cit.tum.de/cps/members/prof-dr-ing-matthias-althoff/ ). Besides excellent skills for conducting innovative science, the candidate should also be talented in implementing research results on a real robot and lead teams of students.

Our Offer

PhD remuneration will be in line with the current German collective pay agreement TV-L E13 (around 4600 Euros/month in the first year, 4900 Euros/month second year). The Technical University of Munich is an equal opportunity employer committed to excellence through diversity. We explicitly encourage women to apply and preference will be given to disabled applicants with equivalent qualifications.

Contact

International candidates are highly encouraged to apply. Please submit your complete application (in English or German) via our application form: https://wiki.tum.de/display/cpsforms/Ph.D.+Application . Fill out all mandatory fields (*) and kindly use “Identification of CPS” as the “Title of Position”. Please do not include a cover letter.

Further similar job offerings will be announced on https://www.ce.cit.tum.de/cps/open-positions/ .

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.