Summer Student 2027 - Risk, Simulation and Digital Evidence

We are looking for students in their 3rd or 4th year of studies who are interested in simulation, complex systems, uncertainty and the future of safety-critical technology.

Modern engineering systems are increasingly supported by simulations, digital twins, AI models and large volumes of operational data. A fundamental challenge is understanding when these models can be trusted and how their results can be used to support important engineering and safety decisions.

In this project, you will explore how simulations, risk assessments and operational data can be used to build confidence in complex engineering systems.

Working together with students focusing on assurance and system understanding, you will investigate questions such as

• How can we model and understand uncertainty in complex systems?
• How can simulations be used to support engineering decisions?
• What makes a digital twin trustworthy?
• How can evidence be generated, validated and communicated?
• How can we determine whether a model is sufficiently accurate for its intended purpose?
• How can future classification and certification processes make use of simulation-based evidence?

The work combines elements of simulation, risk analysis, uncertainty quantification, AI-enabled engineering and decision support for complex technical systems.

#summerjob

Working together with students, focusing on simulation and risk analysis, you will investigate questions such as

• How can we understand the impact of design changes, software updates or maintenance actions?
• How can requirements be traced throughout the lifecycle of a system?
• What information is needed to justify confidence in a safety-critical system?
• How can engineering evidence be structured and updated as systems evolve?
• How can future classification and certification processes become more digital, dynamic and data-driven?

The work combines elements of systems thinking, software engineering, safety, AI-enabled engineering and decision support for complex technical systems.

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.

We are looking for students with interest in

• Engineering Physics
• Applied Physics and Mathematics
• Computer Science
• Marine Technology
• Engineering Cybernetics
• Nuclear Engineering
• Data Science

Experience with some of the following is beneficial

• Numerical methods
• Statistics
• Scientific computing
• Simulation and modelling
• Python programming
• Machine learning
• Risk analysis
• Uncertainty quantification

Interested? How to apply

To be considered for this role, please register your CV, application letter, and grade transcripts in our application tracking system (Oracle) electronically. All documents should be in English. If you choose to apply for more than one role in DNV, please state your preference in the application letter.

Please note: if you either decide to withdraw or want to make changes in your application, you will need to submit a whole new application with a new email address. Please have all documents ready before submitting your final application.

Application deadline: 16.10.2026. We will evaluate your application after the deadline.

Any questions? Please contact Ole Christen Reistad, +47 93266908

We are looking forward to reviewing your application!