FAQs
What is the primary focus of the internship position?
The primary focus of the internship is to analyze and evaluate data related to occupant behavior during accidents and to develop and optimize sensor fusion algorithms for improving restraint systems like airbags and seatbelts.
What are the required qualifications for applicants?
Applicants must be students in fields such as vehicle engineering, computer science, mechatronics, electrical engineering, mechanical engineering, or comparable studies, with good academic performance and practical experience in at least one area of sensor technology.
What programming skills are necessary for this internship?
Applicants should have programming knowledge in languages like Python, MATLAB, or C++, as well as experience in machine learning frameworks such as PyTorch and familiarity with ROS 2 and vehicle electronics.
Are there any specific documents needed to apply for this internship?
Yes, applicants must submit a CV, current enrollment certificate, current transcript of grades, and for mandatory internships, a confirmation from the university. Non-EU citizens also need to provide a work permit.
Is there a specific project or task that interns will focus on?
Interns will continue evaluating a data campaign and work on enhancing a prototype vehicle for live evaluation and display of sensor data.
Who can be contacted for more information about this internship?
For more information about this internship, you can contact Brigitte Adam-Huth.
Is this internship position open to international students?
Yes, the internship is open to international students, but they must provide a work permit if they are non-EU citizens.
What tools or software might interns be using during this internship?
Interns will likely use tools and software such as Python (particularly with PyTorch), MATLAB, and possibly ROS 2 for the development and optimization of sensor fusion algorithms.