Master Thesis Opportunity: Computer Vision for Motorsport Video Analysis

About the Opportunity

At Toyota Racing, we are continuously advancing the use of AI and computer vision to unlock insights from complex race environments. We offer an exciting Master’s thesis opportunity focused on state-of-the-art computer vision methods for analysing race video data in the FIA World Endurance Championship (WEC). The goal of this thesis is to enhance an existing automated race-video analysis system by improving its robustness, accuracy, and real-world performance using modern deep learning approaches.

During WEC races, large volumes of video data are generated from multiple cameras and perspectives. These videos contain valuable information about vehicle positions, movements, and interactions within a highly dynamic environment.

Your work will focus on transforming this raw video data into structured and actionable insights by improving current computer vision models.

Key tasks include:

Reviewing and selecting state-of-the-art object detection and video analysis methods
Designing and implementing improvements to an existing baseline model
Enhancing robustness against real-world challenges such as: Occlusions, Lighting variability, Complex camera perspectives, Visually similar vehicles
Evaluating performance improvements using objective metrics
Generating structured outputs (e.g. vehicle detection and relative positioning) for further analysis
Documenting findings, limitations, and recommendations for future development

You will work in a modern machine learning environment, including:

Python-based ML stack (e.g. PyTorch, OpenCV)
Object detection frameworks (e.g. YOLO or similar)
AWS-based data access and processing
Large-scale motorsport video datasets from past WEC events

Duration & Start

Start date: Earliest 1st August 2026

Duration: Minimum of 6 months

Your Profile

Master’s student in Computer Science, Engineering, Data Science, Mathematics, Physics, or a related field
Hands-on experience with machine learning and computer vision in Python
Experience with at least one deep learning framework (preferably PyTorch)
Basic understanding of object detection, image processing, or video analysis
Experience with OpenCV, YOLO-style models, tracking, segmentation, or data annotation is a plus
Strong analytical mindset and ability to evaluate models using objective metrics
Interest in motorsport and applied AI systems is beneficial

Why Join Us

Work on real-world data from top-tier motorsport
Apply cutting-edge AI methods in a high-performance environment
Contribute to systems used in professional race engineering
Gain hands-on experience with production-relevant ML pipelines

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Toyota Motorsport GmbH