Internship: Fast Physics

823 Damen Research Development & Innovation B.V.; Gorinchem; On-site; EUR 13,392 - 17,856; Part time

Benefits offered by this job

Academic mentoring

Travel allowance

Publish research

Extend internship period

Partner hubs visits

Job summary

Damen Research, Development & Innovation in Gorinchem offers an internship focused on accelerating complex simulations for ship performance using machine learning and graph-based AI.

Join the Data Science team as an intern, work with naval architects and partners, and gain academic mentoring while contributing to a high-impact maritime research project.

Qualifications

• Currently pursuing a Bachelor or Master in a technical field.
• Experience with Python and deep learning frameworks such as PyTorch or TensorFlow.
• Familiarity with 3D geometry formats or CFD data.

Responsibilities

• Support ML-based frameworks, focusing on geometric deep learning and graph neural networks.
• Preprocess CFD data and ship hull geometries.
• Run experiments in Python using PyTorch.
• Collaborate with data scientists, naval architects, and external partners.
• Document results and present findings regularly.

Skills

Python

PyTorch

TensorFlow

Education

Bachelor or Master in Mechanical Engineering, Applied Mathematics, Computer Science, Data Science or related technical field

Job description

We are Damen, a shipbuilding company that aims to become the world's most sustainable and digitally connected shipyard. Our Research, Development & Innovation department develops cutting‑edge data and AI solutions for ship building and maritime operations. This internship is part of a strategic project to accelerate complex simulations for ship performance using machine learning and graph‑based AI.

Internship overview

The role is an intern position within the Data Science team, located in Gorinchem. The internship follows a thesis/graduate internship structure and may start from September onwards.

Key responsibilities

• 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.
• Collaborate with Data Scientists, naval architects, and external partners such as MARIN.
• Document results and present findings to the team regularly.

Qualifications

• Currently pursuing a Bachelor or Master in Mechanical Engineering, Applied Mathematics, Computer Science, Data Science or a related technical field.
• Experience with Python and, ideally, deep learning frameworks such as PyTorch or TensorFlow.
• Familiarity with 3D geometry formats or CFD simulation and numerical data.
• Strong interest in physics‑based modeling and applying AI to engineering problems.
• Fluent communication in English.

Benefits and support

• Academic mentoring throughout the internship.
• Internship/graduation fee and travel allowance 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.
• Possibility to publish research and extend the internship period.
• Optional visits to partner hubs or research centres (e.g., MARIN in Wageningen) depending on project needs and availability.

Additional information

Due to housing issues we cannot accept international students that do not have accommodation in the Netherlands yet.

Application

Send your motivation letter, résumé and additional materials to [e-mail]. Please apply through the Apply button; we cannot accept applications by email due to GDPR reasons.