Master thesis - Vision Foundation Models enhanced Vision-Language Model 3D Spatiotemporal Reasoning

The opportunity to work with state-of-the-art deep learning architectures at the intersection of vision and language. - Access to large-scale autonomous driving datasets and premium GPU computing infrastructure (e.g., A100 40-80Gb clusters). - Close collaboration with researchers working on next-generation AI for autonomous vehicles. - A chance to contribute to an active research area with the potential for scientific publication. **Who are we looking for?** We are looking for a Master’s student 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 and/or natural language processing - PyTorch or similar frameworks - Autonomous driving or robotics The planned thesis start is January 2027. 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** Jesper Eriksson, [jesper.ericsson@scania.com](mailto:jesper.ericsson@scania.com); Thomas Gustafsson, [thomas.gustafsson@scania.com](mailto:thomas.gustafsson@scania.com); Mohammad Nazari, [mohammad.nazari@scania.com](mailto:mohammad.nazari@scania.com); Hiring Manager: Maria Linnarsson, [maria.linnarsson@scania.com](mailto:maria.linnarsson@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. **References** 1. [Haotong Lin, Sili Chen, Jun Hao Liew, Donny Y. Chen, Zhenyu Li, Guang Shi, Jiashi Feng, and Bingyi Kang. Depth Anything 3: Recovering the visual space from any views. arXiv preprint arXiv:2511.10647, 2025](https://arxiv.org/pdf/2511.10647) 2. [Yuechen Luo, Fang Li, Shaoqing Xu, Yang Ji, Zehan Zhang, Bing Wang, Yuannan Shen, Jianwei Cui, Long Chen, Guang Chen, Hangjun Ye, Zhi-Xin Yang, and Fuxi Wen. LaST-VLA: Thinking in latent spatio-temporal space for vision-language-action in autonomous driving. arXiv preprint arXiv:2603.01928, 2026](https://arxiv.org/pdf/2603.01928) 3. [NVIDIA, Niket Agarwal, Arslan Ali, Maciej Bala, Yogesh Balaji, Erik Barker, et al. Cosmos world foundation model platform for physical AI. arXiv preprint arXiv:2501.03575, 2025](https://arxiv.org/pdf/2501.03575) 4. [Yiming Qin, Bomin Wei, Jiaxin Ge, Konstantinos Kallidromitis, Stephanie Fu, Trevor Darrell, and XuDong Wang. Chain-of-Visual-Thought: Teaching VLMs to see and think better with continuous visual tokens. arXiv preprint arXiv:2511.19418, 2025](https://arxiv.org/pdf/2511.19418) 5. [Team Wan, Ang Wang, Baole Ai, Bin Wen, Chaojie Mao, Chen-Wei Xie, et al. Wan: Open and advanced large-scale video generative models. arXiv preprint arXiv:2503.20314, 2025](https://arxiv.org/pdf/2503.20314) 6. [Jianyuan Wang, Minghao Chen, Shangzhan Zhang, Nikita Karaev, Johannes Schönberger, Patrick Labatut, Piotr Bojanowski, David Novotny, Andrea Vedaldi, and Christian Rupprecht. VGGT-Ω. arXiv preprint arXiv:2605.15195, 2026](https://arxiv.org/pdf/2605.15195) 7. [Jie Wang, Guang Li, Zhijian Huang, Chenxu Dang, Hangjun Ye, Yahong Han, and Long Chen. VGGDrive: Empowering vision-language models with cross-view geometric grounding for autonomous driving. arXiv preprint arXiv:2602.20794, 2026](https://arxiv.org/pdf/2602.20794) 8. [Jin Yao, Dhruva Dixith Kurra, Tom Lampo, Zezhou Cheng, Danhua Guo, and Burhan Yaman. VLGA: Vision-language-geometry-action models for autonomous driving. arXiv preprint arXiv:2606.12396, 2026](https://arxiv.org/pdf/2606.12396v1) Publication date: 1.10.2026 - 30.11.2026 (applications evaluated continuously) Requisition ID: 33772 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/1443722933/?locale=en_US)