Scientist Innovator AI based World Modelling & Vehicle Control

De positie

We are looking for an extension of the World Modelling and Vehicle Control team, with a strong foundation in AI-based environmental perception, multi-sensor fusion and state estimation for automated driving systems. The ideal candidate should bring a (solid) experience in sensor fusion methodologies, advanced filtering and estimation techniques and AI-driven scene understanding. Hands-on experience with Python, MATLAB, ROS, and C++ is essential, together with the ability to translate algorithms into robust and efficient implementations in real-world prototypes. Experience in systems

engineering for 'safety-by-design' is highly appreciated. A genuine passion for perception systems and AI-systems, a practical and proactive mindset, and the drive to continuously improve system performance are key.

Tasks/responsibilities

We are seeking a researcher skilled in AI-based perception and world modeling for vehicle and surrounding environment states (estimation and prediction).

• Conduct applied research in AI-based environmental perception, world modeling, and state estimation, proposing and developing novel concepts that bridge scientific innovation and industrial relevance
• Design, implement, and evaluate advanced algorithms, e.g. multi-sensor fusion for localization, road modeling, drivable space detection, feature mapmatching and scan registration from proof-of-concept to real-time prototypes
• Plan, execute, and analyze testing activities for new concepts, including vehicle instrumentation, data collection, simulation, and on-vehicle validation
• Derive functional requirements and 'safe-by-design' frameworks for key autonomy function clusters such as localization, road and environment modeling, object detection and tracking.
• Disseminate work or research outcomes through events, workshops, conference or journal publications, technical reports, and presentations, while collaborating closely with colleague to ensure practical implementation and technology transfer to customer projects.

Over het bedrijf

Our growing mobility demands coincide with unprecedented societal and environmental challenges. The department TNO Integrated Vehicle Safety (IVS) is part of the unit Mobility and Built Environment (MBE) in which we work on big societal

challenges in the field of transport, infrastructure, and housing. At IVS we develop technology and assessment methodologies to accelerate the deployment of Connected and Cooperative Automated Mobility (CCAM) systems that contribute to ‘zero calamities’, ‘zero emissions’ and ‘zero loss’. We support industrial partners and policymakers in their innovation processes for smart vehicles and complex CCAM systems that enhance our mobility and logistics.

In order to make our vehicles and mobility system safer, more sustainable and more efficient, IVS combines extensive knowledge on vehicle automation technologies with innovative safety assessment methodologies.

Wat breng jij

• Educational background: You have minimally a master's degree or similar experience in Mechanical engineering or Robotics with a focus on AI-based environmental perception and world modeling.
• Experience: You have experience within robotics or automotive research domain. Experience with state estimation and filtering techniques is a pre.
• Programming proficiency: Experience with programming in C++ and/or Python is a pre.
• Enthusiastic learner: You are eager to learn more about your research topic and keep yourself up to date with the latest developments by actively engaging with recent literature.
• On-site presence: You can be in the office in Helmond for a minimum of 50% of your working week on average.
• Effective communication: You can articulate your work clearly to your colleagues, which will help with collaborating with colleagues.
• Writing and presentation skills: You have mature writing and presentation skills in Dutch and English, enabling you to author papers and to present your work at conferences.
• Team collaboration: You can work effectively in a team setting, collaborating with colleagues and external partners.