Summer Student 2027 - Risk, Simulation and Digital Evidence

DNV; Oslo; On-site; NOK 201,000 - 335,000; Part time

Benefits offered by this job

Equal Opportunity Employer

Job summary

DNV invites students in their 3rd or 4th year to join a summer project focused on simulation, risk analysis, uncertainty, and the future of safety-critical technology. You will work with digital twins, AI-enabled engineering, and decision support to understand when models can be trusted and how evidence supports critical decisions.

The role blends simulation, risk analysis, uncertainty quantification, and data-driven engineering to explore how to generate, validate and communicate evidence for

Qualifications

• Interest in simulation, risk analysis, and uncertainty quantification.
• Willingness to explore how simulations and data support safety-critical decisions.
• Curiosity about digital twins and evidence-based engineering.

Responsibilities

• Explore how simulations, risk assessments and data can build confidence in complex systems.
• Investigate uncertainty modelling and how evidence is generated and validated.
• Examine how design changes, maintenance actions, and software updates impact safety-critical systems.

Skills

Numerical methods

Statistics

Scientific computing

Simulation and modelling

Python programming

Machine learning

Risk analysis

Uncertainty quantification

Education

Engineering Physics

Applied Physics and Mathematics

Computer Science

Marine Technology

Engineering Cybernetics

Nuclear Engineering

Data Science

Tools

Python

Job description

About Us

We are the independent expert in assurance and risk management. Driven by our purpose, to safeguard life, property, and the environment, we empower our customers and their stakeholders with facts and reliable insights so that critical decisions can be made with confidence.

As a trusted voice for many of the world's most successful organizations, we use our knowledge to advance safety and performance, set industry benchmarks, and inspire and invent solutions to tackle global transformations.

About The Role

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

What we offer

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.

About You

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

Security and compliance with statutory requirements in the countries in which we operate is essential for DNV. Background checks will be conducted on all final candidates as part of the offer process, in accordance with applicable country-specific laws and practices.