Master Thesis in Map Uncertainty in Autonomous Driving
Master Thesis in Map Uncertainty in Autonomous Driving
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Job Description
Are you passionate about the future of autonomous driving We are seeking a talented and motivated individual to join our team of experts dedicated to advancing the capabilities of autonomous vehicles. In this role you will play a crucial part in developing cuttingedge endtoend (E2E) models that enhance the performance of autonomous driving systems particularly in challenging environments where highquality maps are not available.
- You will collaborate with a team of engineers and researchers to design and implement advanced E2E models for autonomous driving.
- Furthermore you will focus on improving model performance in scenarios that rely on raw sensor inputs or lowquality maps enabling the vehicle to infer its surroundings effectively.
- In addition you will conduct experiments and analyze data to identify areas for improvement and optimize model accuracy and reliability.
- You will stay uptodate with the latest advancements in autonomous driving technology and contribute innovative ideas to the team.
- Finally you will document findings and present results in a publishable manner as well as work on opensource benchmarks and datasets.
Qualifications :
- Education: Master studies in a relevant field or comparable with very good grades
- Experience and Knowledge: in implementing machine learning applications in Python with PyTorch TensorFlow or JAX
- Personality and Working Practice: an openminded and reliable individual who is eager to learn
- Languages: fluent in English
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
Andreas Look (Functional Department)
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
