Are you passionate about robots taking over the world? Then look no further! We are currently looking for a highly motivated graduate to join our autonomous car research team in Böblingen close to Stuttgart, Germany.
Current sensors such as stereo cameras or lidar often malfunction in adverse weather where the accident risk is very high. Within two publicly funded projects VVM and AI-See, we experiment with novel neural network architectures such as generative adversarial networks (GAN) and sensor fusion networks to enhance disturbed sensor streams and to make object detection robust in adverse weather. Due to the rarity and extreme variance of bad weather scenes, it is of utmost importance for the validation and further development of deep neural networks to improve the data basis and to render new scenes efficiently as well as realistically. To begin, we will explore how we can improve these simulation techniques through novel learning approaches and how they can be applied to the latest object detection or sensor fusion algorithms to further enhance the safety of our autonomous driving fleet in the future.
Moreover, we apply our algorithms onto latest innovative sensor technologies developed in the project to enable autonomous cars to drive in every situation. You can expect plenty of GPU resources, car loving nerds, thriving international collaborations and the occasional cake (you need to bring one too).
The final thesis selection is made in close consultation with you, the university and us.
