Master Thesis Projects in AI Tooling & Infrastructure

🧠 Build the AI Backbone Behind Safer Autonomous Driving

This year, we’re trying something a little different to make it easier for you to explore and apply for our master thesis projects. Instead of separate ads for every topic, we’ve grouped all projects into three main clusters — each focused on a different part of autonomous driving. You’re welcome to apply to one, two, or all three clusters if you like, but later in the application process, we’ll ask you to prioritize the projects you’re most excited about, in each cluster.

Let’s take a closer look at what this cluster is all about:

Behind every intelligent decision an autonomous vehicle makes is a powerful ecosystem of data, tools, and infrastructure. In this master thesis cluster, you’ll design the platforms and frameworks that enable large-scale AI development — from data pipelines and simulation to distributed learning and knowledge transfer.

Your work is more than engineering — it enables everything else. The systems you create will help perception, planning, and decision-making models train faster, scale smarter, and continuously improve, forming the foundation of safer autonomous driving.

🔬 AI Tooling & Infrastructure: Thesis Projects (Cluster B)

Here are the master thesis projects offered in this cluster — each topic below is a separate project you can apply for:

• Project 1: 📊 Compression of LiDAR point clouds for visualization – Develop efficient compression to make large sensor datasets easier to visualize, store, and process.
  
• Project 2: ⚙️ Scalable Data Engine for Perception Tasks in Autonomous Driving – Build high-performance data pipelines for large-scale training and evaluation.
  
• Project 3: 👁️ Generation of naturalistic synthetic eyes – Create realistic synthetic perception data to support safer, more robust model training.
  
• Project 4: 🌐 Scalable Federated Learning for Autonomous Driving with Self-Supervision – Enable distributed training across fleets while preserving privacy and improving scalability.
  
• Project 5: 📶 Communication-Efficient Federated Learning for Autonomous Vehicles – Design solutions that minimize communication overhead while maintaining model performance.
  
• Project 6: 🔄 Efficient Knowledge Transfer in Heterogeneous Autonomous Driving Systems – Explore strategies to share learned knowledge between different vehicle platforms and models.
  
  

Depending on which project you’re offered, you’ll get to work on designing and implementing AI infrastructure components that power large-scale development. You’ll handle real-world data, contribute to scalable training pipelines, and explore advanced techniques such as federated learning, simulation, and knowledge transfer. Throughout the projects, you’ll collaborate closely with experienced researchers and engineers — and the results of your work will directly contribute to accelerating the development of safer, smarter autonomous vehicles.

We offer several master thesis projects across three clusters:

• Sensing & Perception – how the car sees and understands the world
• AI Tooling & Infrastructure (this one) – the data, platforms, and tools that power autonomous systems
• Planning, Decision-Making & Safety – how the car predicts, plans, and acts intelligently

Each cluster has its own job ad and a detailed project PDF with background on all topics. You’ll receive the PDF in a separate email after you apply to help you explore projects in depth.

🎓 So Who Are We Looking For?

Passionate and curious Master’s students from (including but not limited to):

• Computer Science / Software Engineering
• Machine Learning / Artificial Intelligence
• Data Science / Big Data
• Distributed Systems / Cloud Computing
• Embedded Systems / Autonomous Systems
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