Autonomous Driving Perception & World Models Master Thesis

Zenseact; Göteborgs kommun; On-site; SEK 179,000 - 268,000; Full time

Job summary

Zenseact invites Master’s students to join Cluster A in Gothenburg, Sweden, for an on-site master thesis in autonomous driving perception and world-model research. You will combine ML research with hands-on experiments using real sensor data and modern compute resources.

We welcome discussion on project options and encourage collaboration with experienced researchers and engineers. Spring 2027 thesis period, on-site in Gothenburg with eligibility to study in Sweden.

Qualifications

• Pursuing a Master’s in Computer Science, AI, ML, Robotics, Engineering Physics, EE, Applied Mathematics, or related field.
• Strong Python programming skills.
• Solid ML fundamentals and experience with data-driven experiments.
• Ability to read scientific literature.
• Strong English communication skills.

Responsibilities

• Review state-of-the-art research.
• Work with large-scale sensor datasets.
• Design and run deep-learning experiments.
• Train and evaluate neural networks.
• Build perception and world-model architectures.
• Analyze model behavior and failure cases.
• Present findings and recommendations.

Skills

Python

Machine learning fundamentals

Data & experimentation

Scientific literature

English communication

Education

Master’s degree in CS/AI/ML or related field

Tools

PyTorch

TensorFlow

Job description

Zenseact invites Master’s students to join Cluster A in Gothenburg, Sweden, for an on-site master thesis in autonomous driving perception and world-model research. You will combine ML research with hands-on experiments using real sensor data and modern compute resources.

We welcome discussion on project options and encourage collaboration with experienced researchers and engineers. Spring 2027 thesis period, on-site in Gothenburg with eligibility to study in Sweden.