10 student English-speaking jobs in Cologne

Outstanding students may be offered the opportunity to extend their collaboration as a working student ... WHAT YOU OFFER enrolled student in the field of plant science or alternatively IT along with first agronomic

What to expect You will work at the intersection of machine learning, biomechanics, and vehicle safety. In this project, you will focus on generating human body model motion, with an emphasis on modeling, control, and movement patterns.

flight testing Documentation of the workflow and results Your profile Above average enrolled master student

concept on flight hardware (HiL) Flight test the algorithm Your profile Above average enrolled master student

What to expect In our modern society localization systems play an important role and people and industries depend on their availability. It is therefore desired to have a localization system that is available in all environments. For outdoor environments accurate localization is provided by globally available satellite-based systems such as GPS and Galileo.

What to expect A Multi-Agent System is a network of physically uncoupled subsystems that are connected via a communication structure. To ensure the scalability and availability of such systems, the agents are controlled decentrally by networked controllers.

What to expect At the DLR Institute of Communications and Navigation we conduct research on different methods for precise and reliable localization of trains. To evaluate these methods, we have collected data from different kinds of sources (e. g. video cameras, GNSS receivers, magnetic field sensors, accelerometers).

What to expect At the Innovation Centre for Small Aircraft Technologies in Würselen, DLR is shaping the future of aviation by researching cutting-edge solutions for electric flight.

Product Management Entry level Professionals Location France City/region Meudon La Foret Cedex Working Student

What to expect In the DLR Project “Agile hochratenfertigung und optimierte inspektion für Kleinflugzeuge (AUDITOR)”, we aim to reduce the number of required material testing through a data-driven approach. Incorporating machine learning (ML) models could allow us to accelerate composite structure development while reducing associated costs and testing efforts.