Internship or Graduation: Fast Physics Project

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About us

Damen aims to become the world's most sustainable and digitally connected shipyard. The Research, Development & Innovation (RD&I) department develops and implements the technology and know-how to achieve these ambitions. We actively assist the business in creating an innovative product portfolio and provide forward-thinking guidance to improve the quality and performance of Damen's products and services.

You will be joining the Data Science team within Damen RD&I located in Gorinchem. Our department focuses on applying cutting-edge data and AI solutions to Damen’s shipbuilding and maritime operations. The team includes domain experts in physics-informed machine learning, simulation acceleration, predictive maintenance, computer vision and operational analytics.

This internship is part of a strategic project aimed at accelerating complex simulations for ship performance using machine learning and graph-based AI.

The role

As an intern, you will work on the Fast Physics project, which aims to drastically reduce the runtime of high-fidelity computational fluid dynamics (CFD) simulations of ship hulls. These simulations are essential in predicting how a vessel behaves in water, but they can take hours or days to compute.

Instead of running time-consuming physics-based simulations, we want to use Graph Neural Networks (GNNs), a type of machine learning model that can learn from geometric data, to quickly estimate results like water resistance or flow around the hull. You’ll contribute to training and validating the GNN models that predict physical quantities like ship resistance or flow fields based on geometry and operating conditions. The outcome is a working prototype that can support early-stage design exploration and simulation optimization.

Key accountabilities

• Support the development of geometry-based ML models, focusing on geometric deep learning and graph neural networks.

• Preprocess CFD simulation data and ship hull geometries.

• Collaborate on data preparation pipelines and shape representations

• Run experiments in Python using PyTorch Geometric (or similar frameworks).

• Work closely with in our team together with Data Scientists and external partners such as MARIN.

• Document results and present findings to the team regularly.

Skills & Experience

To be considered for this internship position, you need to have the following credentials:

• Currently pursuing a MSc in Mechanical Engineering, Applied Mathematics, Computer Science, Data Science or a related technical field.

• Have experience with Python, and ideally deep learning frameworks such as PyTorch or TensorFlow.

• Have familiarity with 3D geometry formats or CFD post-processing numerical data.

• Have a strong interest in physics-based modeling and applying AI to engineering problems.

• Communicate fluently in English.

What we offer

• Mentoring at academic level will be available throughout the internship.

• Internship/graduation fee and travel allowance will be paid for the duration of the assignment.

• Opportunity to contribute to a high-impact innovation project in collaboration with leading maritime companies, institutes and universities.

• Research publication is likely possible with a possible extension of the internship period.

• Possibility to visit partner hubs or research centers (e.g., MARIN in Wageningen) depending on project needs and availability

Other

Are you ready to sail into your new adventure at Damen? Let us know in your motivation letter what sparked your interest! Don’t hesitate, send us your letter and resume through the apply button.

Due to housing issues we cannot accept international students that do not have accommodation in the Netherlands yet. This assignment can be taken up as soon as possible or from next semester onwards, September 2025.

Recruiter:

Email:

Please apply through the Apply Button. Due to GDPR reasons we cannot accept applications by email.