Summer Student

The Research Lab team in Trondheim is looking for 2-3 summer students for the Summer 2027 to join us in applying uncertainty quantification (UQ) methods to co-simulation technologies that support the assurance of AI-enabled systems. 

You will work with the Simulation Trust Center (STC), DNV’s cloud-based co-simulation platform, where users can upload, share, integrate, and simulate black-box digital twin models to generate evidence supporting the External Situation Awareness (ESA) system used in maritime autonomous surface ships.

The EAS system is a key enabler of future autonomous surface ships, providing the situational understanding required for autonomous decision-making. However, ESA systems operate in highly uncertain environments, where uncertainty arises from the wide range of operating conditions encountered at sea, as well as the inherent variability and unpredictability of the AI-enabled components and the surrounding environment. Uncertainties associated with individual components within ESA can propagate through the system and affect overall performance and decision-making. Quantifying and understanding these uncertainties is therefore essential for assessing and assuring the reliability of ESA systems as well as creating trust in the evidence generated by STC.

The summer students will work on estimating uncertainties in different types of black-box models within a co-simulation environment. They will also develop a cloud-based service integrated with STC to configure, analyze, and visualize the results, providing a better understanding of how uncertainties propagate through complex systems.

#summerjob

Responsibilities

What we offer:

• An opportunity to work on real industry challenges and real industry data.
• Directly contribute to ongoing research.
• Valuable and real-life experience through our projects
• Meet other young professionals through established networks and informal events
• Opportunity to build a professional network
   

DNV is an Equal Opportunity Employer and gives consideration for employment to qualified applicants without regard to gender, religion, race, national or ethnic origin, cultural background, social group, disability, sexual orientation, gender identity, marital status, age or political opinion. Diversity is fundamental to our culture and we invite you to be part of this diversity. 

Qualifications

Who are we looking for?

We are looking for curious and motivated students who are interested in AI and machine learning methods, uncertainty quantification, digital twins and simulation-based development.