Internship: Anomaly Detection Smart Maintenance

About the Role

We are an open-minded department within Damen’s RD&I and we are looking for a Data Science intern to join our Smart Maintenance project. The internship focuses on developing AI that detects abnormal equipment behavior on board vessels before it leads to failure or unplanned downtime. As an intern you will work on a dedicated research topic selected in collaboration with the team – such as model transferability across vessels, reliable anomaly detection, health trending, explainable AI or defining healthy operation – that strengthens the anomaly‑detection pipeline from data selection to deployment.

• Support the development and improvement of ML‑based anomaly detection models for vessel equipment.
• Preprocess and analyse sensor/time‑series data from onboard systems.
• Run experiments in Python, evaluating model performance against real and/or simulated data.
• Work closely with Data Scientists, maintenance engineers and vessel operations stakeholders.
• Document results and present findings to the team regularly.

• Model transferability across vessels: adapting a model trained on one vessel to others.
• Reliable anomaly detection: reducing false alarms and handling transient events.
• Health and degradation trending: identifying gradual performance degradation.
• Explainable AI and fault diagnosis: making models explainable and supporting root‑cause analysis.
• Defining “healthy” operation: selecting and validating representative data under normal conditions.

• Currently pursuing a Bachelor or Master in Data Science, Applied Mathematics, Computer Science, Mechanical/Electrical Engineering or a related technical field.
• Ideal combination of data science and mechanical/electrical engineering background.
• Experience with statistics, Python and preferably machine learning (e.g., LSTMs) or time‑series analysis.
• Interest in predictive maintenance, sensor data or industrial/marine systems.
• Comfortable working with real‑world operational data.
• Fluently communicates in English.

• Mentoring at academic level throughout the internship.
• Internship/graduation fee and travel allowance for the duration of the assignment.
• Opportunity to contribute to a high‑impact predictive maintenance project used in real vessel operations.
• Possibility of research publication and extension of the internship period.
• Exposure to a multidisciplinary team combining data science and maritime engineering expertise.

Due to housing issues we cannot accept international students that do not have accommodation in the Netherlands yet. Remote work is not an option.