Fraunhofer EMFT conducts cutting-edge applied research on sensors and actuators for people and the environment. The about 150 employees in the three locations in Munich, Oberpfaffenhofen and Regensburg possess impressive long-term experience and wide-ranging know-how in the fields of microelectronics and microsystem technology. The technology offering of the research institute ranges from semiconductor processes, MEMS technologies and 3D integration to foil electronics. These nano- and microtechnologies are the basis for the other competence areas at Fraunhofer EMFT: sensor solutions, safe and secure electronics, and micropumps. The interdisciplinary interaction of these competencies enables the development of truly novel solutions to meet the current challenges facing our society.

The Machine Learning Enhanced Sensor Systems group conducts research in the field of robotics on the topics of environment and object recognition and classification using radar, lidar and stereo cameras, as well as the gripping of sensitive objects using visual and tactile feedback. For this purpose, a mobile robot arm with 7 axes, various grippers and different optical systems (radar, lidar, stereo camera) were purchased. Possible applications for the robot are in the areas of smart farming, such as harvesting apples, in industrial robotics, where safety plays an important role, and in medical technology, e.g. for handling medical equipment. The group has started to build up expertise in the field of robotics in the successfully completed "RoboMove3D" project and would now like to expand this expertise. We are therefore looking for a student who has already gained experience in working with robots and can quickly get to grips with the current setup. In return, students will have the unique opportunity to work more or less exclusively on the robot during their Master's thesis.

Are you passionate and driven by this topic? If so, apply now and support our team in research and development with immediate effect!

What you will do

•    Integration of the robot, the grippers and the optical and tactile sensors via ROS
•    Implementation of a non-trivial gripping task taking into account the sensory feedback
•    Implementation of a ROS node for tactile sensors
•    Application of machine learning methods for object recognition and optimization of the gripping process

What you bring to the table

•    Studies at a university or college in the field of electrical engineering and information technology, computer science, mechanical engineering or a comparable field of study
•    Good knowledge of Python
•    C++ knowledge is an advantage
•    Good knowledge of robotics and working with ROS/ROS2
•    Initial experience with machine learning topics
•    Independent way of working and high motivation

What you can expect

We offer you a challenging and varied research role with responsibility and creative freedom.
In our open-minded team, you can set your own priorities, realize your ideas in projects and develop yourself scientifically, professionally and personally. You will be supported by various offers from the Fraunhofer-Gesellschaft to help you combine family, work and career development in the best possible way.

The weekly working time is max. 20 hours. We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Remuneration according to the general works agreement for employing assistant staff.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future. 

Interested? Apply online now. We look forward to getting to know you!

Questions about this position will be gladly answered by: 
Florian Rieger 
Machine Learning Enhanced Sensor Systems
florian.rieger@emft.fraunhofer.de 
Tel.: +49 89 54759-557 

Fraunhofer Institute for Electronic Microsystems and Solid State Technologies EMFT 

www.emft.fraunhofer.de 

Requisition Number: 74282                Application Deadline: 09/30/2024