Master thesis - End-to-End Autonomous Driving with Vision Foundation Models and Generative Planning

The opportunity to work with state-of-the-art deep learning methods for autonomous driving. - Access to large-scale driving datasets and modern GPU computing infrastructure. - Close collaboration with researchers working on next-generation AI for autonomous vehicles. - A chance to contribute to an active research area with potential for scientific publication. **Education/program/focus** We are looking for one or two motivated Master’s students in Computer Science, Robotics, Engineering Physics, Electrical Engineering, Applied Mathematics, or a related field. Experience with one or more of the following is beneficial: - Deep learning and machine learning - Computer vision - Generative AI - PyTorch or similar frameworks - Autonomous driving or robotics Number of students: 1 Start date for the thesis work: \[To be agreed\] Estimated time required: 20 weeks, full time (30 credits) **Contact persons and supervisors** Truls Nyberg, [truls.nyberg@scania.com](mailto:truls.nyberg@scania.com); Samir Khays, [samir.khays@scania.com](mailto:samir.khays@scania.com); Giulia D’Ascenzi, [giulia.dascenzi@scania.com](mailto:giulia.dascenzi@scania.com) Hiring Manager: Magnus Granström, [magnus.granstrom@scania.com](mailto:magnus.granstrom@scania.com) **Application** Your application must include a CV, personal letter, and transcript of grades. A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified. **Publication date** from - to 2026-10-07–2026-11-30 Requisition ID: 33866 Number of Openings: 1.0 Part-time / Full-time: Full-time Permanent / Temporary: Temporary Country / Region: SE Location(s): Södertälje, SE, 151 38 Required Travel: 0% Workplace: Hybrid [Apply now »](https://jobs.scania.com/talentcommunity/apply/1445070333/?locale=en_US)