Internship / Master's thesis Deep Learning for autonomous driving (f/m/d)
Indexed description
Possible Tasks within this Role
- Development and implementation of concepts to systematically generate traffic scenarios with anomalies or adverse conditions
- Research and analysis of current literature on the generation of anomalous data
- Practical investigations of data-driven deep learning methods for scenario generation for a selected use case
- Evaluation of the quality of the generated data according to self-developed or predefined criteria
- Documentation and presentation of the results
- Master’s student in Computer Science, Robotics, Data Science, Mathematics, Physics, Engineering Sciences or a related qualification
- Very good to good academic achievements
- Strong analytical and conceptual skills, familiarity with scientific methods
- Ability to work independently and in multidisciplinary teams, highly motivated
- Good knowledge of an object-oriented programming language, preferably Python, and of deep learning methods
- Profound experience with deep learning libraries like PyTorch in the context of research projects
- Ideally practical experience in the area of driver’s assistance systems or automated driving
- Fluent in English (at least language level B2)
- Cover letter and CV
- 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
The gross hourly wage for internships (including mandatory internships) and thesis projects
is equal to the current minimum wage.
Contact person for this posting: Hartmut Fromm
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