Internship: Fast Physics

Qabird

Gorinchem

On-site

EUR 12,276 - 16,740

Full time

14 days+

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Benefits offered by this job

Mentoring at academic level
Travel allowance
Internship/graduation fee
Publication potential
Visit partner hubs

Job summary

Damen RD&I in Gorinchem invites a summer intern to join the Data Science team. You will work on the Fast Physics project to drastically reduce CFD runtime using geometric deep learning, learning from vessel designs to estimate water resistance and flow around hulls.

You will contribute to training and extending the framework, preprocessing CFD data, and running Python experiments. Mentoring at academic level is provided, with potential for thesis extension and collaboration with MARIN.

Qualifications

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

Responsibilities

  • Train, validate, and extend ML framework for multiple ship types and fidelity levels.
  • Preprocess CFD simulation 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 to the team.

Skills

Python
PyTorch
TensorFlow
3D geometry
CFD data
English

Education

Bachelor or Master in Mechanical Engineering
Applied Mathematics
Computer Science
Data Science

Tools

None

Job description

We offer you an Ocean of Possibilities. Join our family.

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.

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.

Key accountabilities
  • 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
  • Is currently pursuing a 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.
  • Is full‑time available to take on this project as a summer internship, with the possibility to extend to a thesis or graduation project.
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: liselotte.van.veenendaal@damen.com

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

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