Industrial PhD Student in World Models and Autonomous Driving

Scania Nederland B.V.; Stjärna; Hybrid; SEK 420,000 - 540,000; Full time

Benefits offered by this job

Wellness allowance

Bonus

Flexible hours

Company car leasing

Employee events

Job summary

TRATON Group R&D invites applications for an Industrial PhD Student project focusing on world models and autonomous driving. You will develop end-to-end trainable models that map multimodal sensor data to compact representations to support real-time trajectory planning.

The role emphasizes robust, scalable solutions for heavy‑duty autonomous trucks. You will be a PhD student at KTH under professors Patric Jensfelt and Olov Andersson, employed by TRATON with employee benefits, while pursuing

Qualifications

• Master’s degree in a technical field with strong mathematical foundations.
• Proven programming skills and interest in ML, robotics, and autonomous systems.
• Fluency in English; ability to work in international research settings.

Responsibilities

• Develop end-to-end trainable models that transform multimodal sensor data into representations for real‑time trajectory planning.
• End-to-end navigation and safety-focused decision-making under industrial constraints.
• Collaborate with TRATON/RPL and KTH researchers to advance autonomous truck research.
• Communicate findings through scientific writing and publications.

Skills

Python

C++

Machine learning

Computer vision

Robotics

Simulation

Scientific writing

Education

Master's degree in a relevant technical field

Job description

Industrial PhD Student in World Models and Autonomous Driving

TRATON is a group of strong brands with a shared mission: transforming transportation together to create the future of sustainable transport solutions. Within TRATON, we include MAN, Scania, Volkswagen Truck & Bus, and International. As part of a global team of industry experts, you get to think bigger, experience more, and reach further.

Together, we have the power to transform transportation.

Our values – customer first, respect, team spirit, responsibility, and elimination of waste – are at the heart of everything we do.

Role Summary

Have you ever thought about how effortlessly we navigate through the world? Most of the time, we move through familiar environments almost automatically, relying on our senses and an internal understanding of how the world works. Yet when something unexpected happens, we immediately switch to a more deliberate mode of reasoning. Can we build autonomous vehicles that do something similar while maintaining the level of safety required for real‑world deployment?

The goal of this project is to endow our vehicles with the ability to represent and understand the world in order to safely navigate through it. This will entail developing end‑to‑end trainable models that transform multimodal sensor data into compact and informative representations that support real‑time trajectory planning. A particular focus of the project is understanding how compact world representations can support real‑time decision‑making under realistic industrial constraints.

Heavy‑duty vehicles introduce challenges that differ from passenger cars. They are often articulated, their mass can vary significantly depending on the load, and they require specialized maneuvers to navigate safely. The models we develop must therefore be efficient, robust, and able to generalize across different vehicle configurations.

This Is Us

Within TRATON Group R&D, you are an important part of something bigger. Joining us means gaining access to the ins and outs of the entire transportation industry. At TRATON, you will work with teams developing autonomous transport solutions, with a particular focus on autonomous trucks that can operate both in confined areas and on public roads. You will work with research engineers as well as other industrial PhD students who like collaborating on great ideas. We will support you in developing your ideas and incorporating them into the TRATON solutions. You will not only have great team support at TRATON, but you will also be a PhD student in the Robotics, Perception, and Learning (RPL) department at KTH, Royal Institute of Technology, where Professor Patric Jensfelt and Assistant Professor Olov Andersson will guide and supervise your doctoral studies.

You will be employed by TRATON on a permanent basis with the same benefits as other TRATON employees, while concurrently being associated with KTH as a PhD student.

Who You Are

We welcome applicants from all backgrounds – your unique experience and perspectives are valuable to us.

You hold a Master’s degree in a relevant technical field, with strong mathematical foundations, proven programming skills, and a clear interest in machine learning, robotics, and autonomous systems. You are curious about how complex systems work and motivated by solving difficult real‑world problems. You enjoy both scientific research and practical engineering, are comfortable working both independently and in teams, communicate clearly, and are fluent in English.

• Programming and software development in Python, C++, or similar languages.
• Machine learning and deep learning.
• Computer vision, multimodal learning, or representation learning.
• Robotics, autonomous systems, planning, or control.
• Simulation and evaluation of autonomous systems.
• Scientific writing, peer‑reviewed publications, or research project experience.

If the project excites you and you believe you can contribute, we encourage you to apply.

TRATON Offers

We offer a dynamic, flexible workplace with hybrid work options, including Scania Sergel and Midway hubs. With a structured development plan and courses, TRATON Group R&D supports your career growth both locally and internationally. Benefits include wellness allowance, bonus, flexible hours, and company car leasing. We also host events for employees and their families, and Stockholm residents enjoy direct access to Södertälje via Scania Job express buses for an easy commute to Södertälje.

Application

We look forward to receiving your application, consisting of your CV. Kindly do not share a cover letter to ensure an efficient and unbiased recruitment process for all parties. Apply as soon as possible, no later than 2026‑07‑30. Screening will take place on an ongoing basis during the application period. Logical and personality tests may be used as part of the selection process, and a background check may be required for this role.

For technical questions about the project, please contact Rafael Valencia ([e-mail]) and Thomas Gustafsson ([e-mail]). For questions regarding the recruitment process, please contact Maria Linnarsson ([e-mail]).

We look forward to your application!