Internship AI Methods Vehicle Safety (f/m/d)

Environment

In the Vehicle Safety Test Technology team, we are responsible for the entire scope of active and passive safety experiments. This also includes the ongoing 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 after this internship.

Possible Tasks within this Role

• Conduct research on condition monitoring of mobile robots, use of time series data with a special focus on physics-informed models

• Identify methods that best meet the project's needs and offer high potential for accurate predictions.

• Develop Python scripts for data processing, analysis, and visualization

• Implement and adapt methods in Python, and conduct experiments with mobile robots for evaluation

• Analyzing and interpreting the results, evaluating the methods and presenting to the supervisor and research team

Qualification requirements

• Students in engineering, computer science, data science or comparable fields of study

• Very good academic performance

• Good programming skills in Python, including the application of OOP principles

• Basic knowledge of relevant ML frameworks such as PyTorch or TensorFlow, as well as data processing libraries such as Pandas

• Interest in integrating technical system understanding and data-based analysis

• German and English language level C1

• Driver's license advantageous

• Independent work and problem solving

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

Keywords

Pattern recognition, FAS, real-time response

Contact person for this posting: Brigitte Adam-Huth