Job summary
This summer position involves working on uncertainty quantification methods for co-simulation platforms supporting AI-enabled maritime autonomous systems. The role provides experience with real industry data and research in simulation-based development and digital twins, enhancing understanding of autonomous system reliability.
Location and work setup
- Location
- Trondheim
- Work setup
- On-site
Responsibilities
Work on estimating uncertainties in various black-box models within a co-simulation environment. Develop a cloud-based service integrated with a co-simulation platform to configure, analyze, and visualize uncertainty propagation in complex autonomous systems. Contribute directly to ongoing research efforts and collaborate within a technical team.
Qualifications
Currently enrolled 3rd or 4th year Bachelor or Master student in Data and AI/ML, Computer Science, Information Science, Mathematics, Marine Technology, Cybernetics, Robotics, or Physics. Strong interest in AI, machine learning, uncertainty quantification, and simulation. Experience with data processing and AI/ML tools such as PyTorch, Scikit-learn, TensorFlow, and knowledge of Bayesian methods. Familiarity with computer vision, ROS, sensor fusion, FMI/FMU, Python programming, cloud platforms (e.g., Microsoft Azure), CI/CD, Kubernetes is advantageous. Good English communication skills. Curiosity, initiative, and collaborative mindset are essential. Applicants lacking some qualifications are encouraged to apply.