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Trajectory planning for autonomous systems in safety-critical situations

05.04.2023, Wissenschaftliches Personal

Tasks and project
As part of a research project, you will be part of a dedicated group developing software for autonomous vehicles. Your research project focuses on enabling efficient and safe trajectory planning in safety-critical scenarios. For this purpose, we focus on modeling and quantifying risks in order to subsequently incorporate them into trajectory planning. The goal is to enable safe and agile behavior of the autonomous vehicle. You will be responsible for the conception, implementation and evaluation of the new algorithms. In addition to your technical work, you will take responsibility for teaching and ancillary tasks and supervise student teams.

Your profile
You are enthusiastic about the topic of autonomous systems and robotics and are motivated to take on responsibility in research. You enjoy working in a loyal and committed team to solve complex problems and dedicate yourself to a topic over a longer period of time.

In summary, you bring with you:

-A Master's degree in a technical field (mechanical engineering, mechatronics, robotics, electrical engineering, computer science, etc.)
-Know-How from lectures in robotics (e.g. environment perception, path and behavior planning, control)
-Very good programming skills (e.g. Python)
-A conscientious and independent way of working
-High motivation and commitment
-Negotiation skills in written and spoken German and English

We offer:
-Full-time position as research associate (TV-L E-13, 100%)
-Integration into the TUM Graduate School for support in doctoral studies
-Future-oriented research area with high (national and international) scientific exchange
-Loyal, reliable and committed team
-Numerous opportunities for professional and interdisciplinary training (e.g. soft-skill seminars)
-Modern working environment and infrastructure
-Possibility to work abroad
-Flexible home office arrangement

How do I apply?
The Autonomous Vehicle Systems Lab aims to increase its percentage of women and therefore strongly encourages qualified women to apply. Severely disabled persons will be given preference in case of equal suitability and qualification.

Please send your complete written application (cover letter, curriculum vitae, high school diploma, bachelor's diploma, master's diploma, confirmation of internships) in German or English in digital form to the following email address: johannes.betz@tum.de

Die Stelle ist für die Besetzung mit schwerbehinderten Menschen geeignet. Schwerbehinderte Bewerberinnen und Bewerber werden bei ansonsten im wesentlichen gleicher Eignung, Befähigung und fachlicher Leistung bevorzugt eingestellt.

Hinweis zum Datenschutz:
Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universität München (TUM) übermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die Übermittlung Ihrer Bewerbung bestätigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben.

Kontakt: johannes.betz@tum.de

Mehr Information

https://www.mos.ed.tum.de/en/afs/career/our-jobs/planning-uncertainty-1/