Internship: Fast Physics

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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 to compute. Instead of running time-consuming physics-based simulations, we use geometric deep learning , a type of machine learning that can learn from vessel designs and quickly estimate results like water resistance or flow around the hull. The outcome is a working prototype that can support early-stage design exploration and simulation optimization.

You will contribute to enhancing the performance of an existing system that predicts physical quantities , such as ship resistance and flow fields , based on geometry and operating conditions. Your primary focus will be on a dedicated topic involving the training, validation, and extension of the framework to support multiple ship types and/ or varying levels of simulation fidelity . The assignment can be a thesis/graduate internship and could start from September onwards .

Key accountabilities

You will be responsible for the following aspects

• Support the improvement of ML -based frameworks , focusing on geometric deep learning and graph neural networks.
• Preprocess CFD simulation data and ship hull geometries.
• Run experiments in Python using PyTorch .
• Work closely in our team together with Data Scientists , domain knowledge naval architects, and external partners such as MARIN.
• Document results and present findings to the team regularly.

Skills & Experience

We are looking for a student who

• Is currently pursuing an Bachelor or Master in Mechanical Engineering, Applied Mathematics, Computer Science, Data Science or a related technical field.
• Has experience with Python , and ideally deep learning frameworks such as PyTorch or TensorFlow.
• Has familiarity with 3D geometry formats or CFD simulation and numerical data.
• Has a strong interest in physics-based modeling and applying AI to engineering problems.
• Communicates 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? Don’t hesitate, send us your motivation letter and resume here.
• Due to housing issues we cannot accept international students that do not have accommodation in the Netherlands yet.

Recruiter

Liselotte van Veenendaal Email

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