Environment

In the Vehicle Safety Test Technology team, we are responsible for the entire scope of active and passive safety testing. This also includes the further development of the test facilities, measuring equipment, analysis methods, software tools, IT systems, and databases required for this purpose. Due to the large amount of measurement data generated, it is necessary to be able to carry out analyses without human intervention. For this purpose, AI algorithms are trained and constantly updated with newly entered data so that the most optimized and meaningful evaluations possible are created. There is the possibility to write a thesis. 

Possible Tasks within this Role

• Support in the further development of data analytics tools and evaluation of measurement data

• Performing condition monitoring and anomaly detection methods of active vehicle safety trials

• Accompanying the evaluation of measurement campaigns

• Helping to maintain and further develop Matlab tools and Python modules for evaluating time series data

• Perform deep learning methods and feature importance analysis on time series data

Qualification requirements

• Students in the master's program in engineering, mathematics, physics, computer science, or a comparable field of study

• Completed basic studies or more than 89 credit points, as well as good to very good academic performance

• Advanced knowledge of statistics, Python, and Matlab

• Proficiency with machine learning modules of Python, e.g., Scikit-learn, Panda, and Numpy

• Basic knowledge of Matlab's signal processing toolboxes is an advantage

• Confident handling of MS Office

• German and English language level C1

• Initiative, independent way of working, and analytical thinking skills

The following documents must be submitted with the application

• Curriculum vitae

• Current certificate of enrolment

• Current transcript of records

• In the case of a compulsory internship, an additional certificate from the university

• Work permit for non-EU citizens