PhD - Predictive Occupancy World Models for End-to-End Autonomous Driving

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch. The Robert Bosch GmbH is looking forward to your application!

Employment type: Limited Working hours: Full-Time Joblocation: Hildesheim The Corporate Research Division is the heart of our innovation. You will be part of the Bosch Research Computer Vision and AI Lab in Hildesheim, Germany, at the forefront of developing the next generation of autonomous systems. We are looking for a passionate and creative PhD candidate to join our team and help shape the future of AI-driven mobility. You will develop a generic predictive occupancy model as the core representation of the driving scene, designing architectures that capture the geometry and semantics of all objects to enable an explicit understanding of 4D world dynamics. Additionally, you will research, implement, and measured novel end-to-end (E2E) driving architectures based on predictive occupancy world models, robust situational awareness and safe navigation. You will develop state-of-the-art perception systems that seamlessly transform raw sensor data into rich spatial representations and driving actions, bridging the gap between perception and automated driving. As part of this role, you will create architectures in which driving decisions are directly based on predictive occupancy world models, ensuring spatially grounded and reliable actions. Last but not least, you will rigorously test your models in simulation and with real-world data, demonstrating improvements in safety, transparency, and performance, and you will publish your findings at leading AI and robotics conferences.

Education: excellent master's degree in Computer Science, Robotics, Artificial Intelligence, Data Science, or a related field that qualifies you for doctoral studies Experience and Knowledge: strong expertise in Deep Learning and Computer Vision (CV), hands-on experience with modern deep learning frameworks (e.g., PyTorch), and proven Python programming skills; experience in 3D Computer Vision, Occupancy Networks, End-to-End (E2E) Driving, World Models, or Sensor Fusion is highly desirable; familiarity with autonomous driving datasets and simulation environments (e.g., CARLA) is considered an advantage Personality and Working Practice: you are a creative and self-driven researcher who enjoys taking ownership of challenging topics, developing innovative ideas comes naturally to you, and you thrive both independently and in technical discussions with colleagues Enthusiasm: you have a genuine passion for solving fundamental AI challenges and are driven to build systems that are not only intelligent but so trustworthy and safe Languages: excellent English skills, German is an advantage

Work-life balance: Flexible working in terms of time, place and working model. Health & Sports: Wide range of health and sports activities. Childcare: Intermediary service for childcare services. Employee discounts: Discounts for employees. Room for creativity: Space for creative work. In-house social counseling and care services: Social counselling and intermediary service for care services.

The recruitment contact or superior will be happy to provide information about the individual benefit plan. .