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.

🧭 Teach Cars to Think, Plan, and Make Safe Decisions

If perception is how an autonomous vehicle sees the world, then planning and decision-making are how it thinks and acts in it. In this cluster, you’ll explore how cars predict the behavior of other road users, make complex decisions under uncertainty, plan safe and efficient maneuvers, and validate that their choices are robust and trustworthy.

Your work will help shape the “brain” behind autonomous driving — turning data and predictions into safe, real-world actions.

🔬 Planning, Decision-Making & Safety: Thesis Projects (Cluster C)

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

• Project 1: 🧠 Hybrid Planner for Complex Driving Scenarios – Design and evaluate planning strategies that combine classical and learning-based methods for challenging traffic situations.
• Project 2: 🧪 Automated Generation of Challenging Driving Scenarios – Develop techniques to automatically create difficult and safety-critical test cases to push autonomous systems to their limits.
• Project 3: 👁️ Object Occlusion Modelling in Object-Level Reinforcement Learning – Investigate how occlusions affect decision-making and improve how vehicles reason under incomplete information.
• Project 4: 📊 Evaluation of Predictors for Safety Assessment – Analyze and benchmark different prediction models to understand their impact on safety and decision-making performance.
• Project 5: 🛠️ Falsification of Safety-Critical Decision and Control Software – Develop methods to uncover weaknesses in decision-making and control logic through falsification and testing.
• Project 6: 🧩 Training End-to-End Planners in Sensor-Level Simulation – Train planning systems directly from raw sensor inputs in simulation environments to bridge the gap between perception and control.

Depending on which project you’re offered, you’ll work on designing, training, and evaluating systems that make autonomous driving safer and more reliable. You might create algorithms that plan optimal trajectories, develop scenario generation tools to test vehicle behavior, or design validation techniques to ensure decisions hold up in the real world. Throughout the projects, you’ll collaborate closely with experienced engineers and researchers — and your work will help build the decision-making intelligence of future autonomous vehicles.

We offer several master thesis projects across three clusters:

• Sensing & Perception – how the car sees and understands the world
• AI Tooling & Infrastructure – the data, platforms, and tools that power autonomous systems
• Planning, Decision-Making & Safety (this one) – 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 the projects in more depth and choose the ones that best match your skills and interests.

🎓 So Who Are We Looking For?

We’re seeking passionate and curious Master’s students from (including but not limited to):

• Computer Science / Software Engineering
• Machine Learning / Artificial Intelligence
• Robotics / Autonomous Systems
• Control Engineering / Mechatronics
• Mathematics / Applied Physics

Because this cluster spans several projects, the required skills vary. When you apply, please list all relevant skills, tools, and knowledge areas — and describe your level of experience with each (e.g., basic, intermediate, advanced). This helps us understand your profile and match you with the project that best fits your background.

🧰 Expected Skills & Experience

Typical skills we look for (you’re not expected to have all):

• Programming (e.g., Python, C++)
• Experience with motion planning, control algorithms, or decision-making systems
• Understanding of machine learning, reinforcement learning, or safety validation methods
• Knowledge of prediction models, scenario generation, or simulation tools
• Familiarity with testing, verification, or safety-critical software development

🌟 What’s in It for You?

• Work on projects that directly shape the decision-making intelligence of autonomous vehicles
• Gain hands-on experience with planning, prediction, and safety validation technologies
• Collaborate with experts and contribute to real-world solutions that improve road safety
• Join a diverse, innovative, and inclusive team shaping the future of mobility

📩 How to Apply?

Submit your CV, motivation letter, and grade transcripts.

• Applying as a pair? Include your partner’s name in the application.
• Planned start: January 2026 (flexible)
• Application deadline: October 31, 2025 (applications reviewed continuously)

📧 For more information, contact: Gabriel Campos, Research Manager – gabriel.campos@zenseact.com

This 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 Difference

We 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 Product

We 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 Heart

We 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, both 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 — we value and respect differences in gender, race, ethnicity, religion or belief, disability, sexual orientation, age, and more.

🕐 Interviews are held on a continuous basis, so we highly recommend that you submit your application as early as possible.