Internship – Anomaly Detection for Smart Maintenance

About the role

Join Damen's Data Science team in Gorinchem to work on the Smart Maintenance project, developing AI‑driven anomaly detection for vessel equipment. You will help turn large volumes of sensor data into reliable signals that support maintenance decisions.

Key responsibilities

• Support development and improvement of machine‑learning based anomaly detection models for shipboard equipment.
• Preprocess and analyse sensor time‑series data from onboard systems.
• Run experiments in Python, evaluate model performance against real or simulated data, and document findings.
• Collaborate closely with data scientists, maintenance engineers, and vessel operations stakeholders.

Required profile

• Currently pursuing a Bachelor or Master in Data Science, Applied Mathematics, Computer Science, Mechanical/Electrical Engineering or a related technical field.
• Interest in predictive maintenance, sensor data, or industrial/marine systems and ability to work with real‑world operational data.
• Fluent communication in English.

Required skills

• Python programming.
• Statistics.
• Machine learning, preferably with LSTMs or time‑series analysis.

What we offer

• Academic mentoring throughout the internship.
• Internship/graduation fee and travel allowance.
• Opportunity to contribute to a high‑impact predictive maintenance project used in real vessel operations.
• Potential for research publication and exposure to a multidisciplinary team.