Job Description
In recent years, Advanced Driver Assistance Systems (ADAS) such as Adaptive Cruise Control (ACC) and lane departure warning have become increasingly popular. However, these systems still have room for improvement in certain scenarios, which requires a systematic search for such scenes during the development phase. Unfortunately, this process requires expensive and time-consuming manual expert labelling to cluster and label these effects.
1. To address this problem, in your Master thesis you will design a machine learning algorithm using continuous-valued input data from radar and camera to classify faulty scenarios in post-processing.
2. Furthermore, you will test and optimize the algorithm using real data.
3. Last but not least, you will integrate the algorithm into an existing validation framework.
Qualifications
4. Education: Master studies in the field of Engineering or comparable
5. Experience and Knowledge: in Python; skills in Deep Learning (Pytorch), driver assistance systems and sensors (radar, camera) are an advantage
6. Personality and Working Practice: anindependent, motivated and reliable person
7. Languages: very good in English and basic in German
Additional Information
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.
Need further information about the job?
Patricia Duran (Functional Department)
+49 711 811 37308
#LI-DNI