Master Thesis Projects in AI Tooling & Infrastructure

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.🧠 Build the AI Backbone Behind Safer Autonomous DrivingBehind 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 ForProject 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 ClustersSensing & Perception – how the car sees and understands the worldAI Tooling & Infrastructure (this one) – the data, platforms, and tools that power autonomous systemsPlanning, Decision-Making & Safety – how the car predicts, plans, and acts intelligentlyEach 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 EngineeringMachine Learning / Artificial IntelligenceData Science / Big DataDistributed Systems / Cloud ComputingEmbedded Systems / Autonomous Systems🧰 Expected Skills & ExperienceBecause this cluster spans multiple topics, requirements vary. In your application, please list all relevant skills/tools and your experience level for each (basic / intermediate / advanced). This helps us match you with the best project.Typical skills we look for (you do not need all of these):Programming in Python, C++ and/or CloudFamiliarity with ML or data-engineering pipelinesExperience with deep learning frameworks (PyTorch, TensorFlow)Knowledge of distributed systems, federated learning, or simulation environmentsInterest in scalability, data infrastructure, or MLOps🌟 What’s in It for You?Contribute to the core infrastructure that powers autonomous drivingHands-on experience with real-world data, scalable AI systems, and advanced toolsCollaboration with industry experts on impactful, production-oriented solutionsJoin a diverse, inclusive team shaping the future of mobility📩 How to Apply?Submit your CV, motivation letter, and grade transcripts.Applying as a pair? Please include your partner’s name in the application.Planned start: January 2026 (flexible)Application deadline: October 31, 2025 (applications reviewed continuously)For questions, contact: Gabriel Campos, Research Manager – gabriel.campos@zenseact.comThis role may involve access to sensitive information, trade secrets, and confidential data. Selected candidates may undergo a background check as part of the recruitment process.More About Zenseact🚗 Our software makes a differenceWe use AI-driven technology to fight traffic accidents and make roads safer. Every year, 1.4 million people lose their lives in traffic — we’re here to change that.🎯 One purpose, one productWe design the complete software stack for autonomous driving and advanced driver-assistance systems. With continuous updates, cars become safer over time — bringing us closer Towards Zero. Faster.❤️ Culture with people at heartWe can only succeed together. Our culture is built on care, trust, and belonging — a place where everyone can grow, be themselves, and do their best, at work and in life.Zenseact works proactively to create a culture of diversity and inclusion, where individual differences are appreciated and respected. To drive innovation we see diversity as an asset, which means we value and respect differences in gender, race, ethnicity, religion or other belief, disability, sexual orientation or age etc.Interviews are held on a continuous basis, so we highly recommend that you submit your application at your earliest convenience.One purpose, one productWe are a software company focused on transforming car safety. By developing a complete software stack for autonomous driving and advanced driver-assistance systems, we aim to eliminate car accidents and make roads safer for all. Founded by Volvo Cars, Zenseact operates globally, with teams in Gothenburg and Lund, Sweden; and Munich, Germany.