慕尼黑工业大学学习系统安全、性能与可靠性教研室博士职位

TUM-LSY Open PhD Positions (m/w/d)

22.12.2025, Academic staff

We are an interdisciplinary team at the Chair of Safety, Performance and Reliability for Learning Systems, and we are looking for exceptional PhD candidates to join our team.

Open PhD Positions

The PhD positions will be full-time (100%, TV-L E13). We are committed to fostering a diverse and inclusive research environment, and we strongly encourage candidates from underrepresented groups to apply. The review process is on a rolling basis. Please refer to the "Application Procedure" section for details on how to apply (application form).

Current PhD Openings • Resilient Communication and Learning-based Control for Embodied Networked Intelligence (6G-life) (ID: TUEILSY-PHD15) • Safe and capable humanoids in interaction-rich scenarios (ID: TUEILSY-PHD12) • Act Based on What You See: Semantically Safe Robot Interaction (ID: TUEILSY-PHD20240930-SSR) • Distributed Multiagent Planning and Control for Large Aerial Swarms in Changing Environments (ID: TUEILSY-PHD20240930-SAS) • Safe Collaborative Manipulation in Cluttered and Dynamic Environments (ID: TUEILSY-PHD20240930-SCMM)

A more detailed topic description can be found at https://www.ce.cit.tum.de/lsy/open-positions/open-phd-positions/ . Requirements • Top-ranked Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); • Being excited to make a real impact with their thesis work in the field of robotics; • Strong programming skills in C++ and/or Python, as well as experience in implementing robot learning algorithms; • A strong background in control theory, machine learning, and/or computer vision; • A proven track record demonstrating strong problem-solving skills and the ability to conduct independent research (e.g., through publications at top venues in robotics, computer vision, machine learning, or a relevant field); • Excellent communication skills in English and ability to work in a dynamic team environment; • Previous experience working with real robots is a plus.

If you do not satisfy all requirements but are very interested in the position, please feel free to apply and/or reach out to us for questions.

Application Procedure Please submit your application package via the following link: http://tiny.cc/lsy-phd-applications . In the application form, you will be asked to submit a package that includes the following documents:

• A personal statement highlighting research interests and relevant experience; • An academic CV including a full list of publications; • Transcripts; • Relevant certificates (e.g., university degrees, additional courses); • Contact information of three referees; • Any additional supporting documents you would like to share with us.

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.

Kontakt: If you have any questions regarding the open positions or the application process, please contact us at contact.lsy@xcit.tum.de and ensure that the posting ID is indicated in the subject line.