Internship: Designing AI Techniques for Discovering Patterns in Operational System Data

Internship assignment: Designing AI Techniques for Discovering Patterns in Operational System Data

Vanderlande systems generate large volumes of data across monitoring platforms, install base reports, site configurations, equipment performance logs and user activity. In theory, this data should provide clear insights into system health, operational performance, and service opportunities. In practice, however, much of this information remains fragmented across different tools and datasets, requiring engineers and service managers to manually interpret signals.

Because these systems evolved separately, valuable relationships between datasets often remain hidden. Extracting meaningful insights therefore requires significant manual effort and domain expertise.

As a result, decision-making is often reactive. Service teams spend time identifying root causes instead of acting on early signals, product teams lack clear feedback from the field, and customers receive insights later than necessary.

Advances in Agentic AI and modern data analysis techniques offer the opportunity to automatically identify patterns across datasets and generate actionable insights for different user groups such as service engineers, operations managers, and product teams.

Research question

How can (Agentic) AI techniques be used to identify meaningful patterns across Vanderlande’s monitoring, install base, site, equipment, and user data to automatically generate actionable, role-specific insights?

Department description

The Digital Services department develops data-driven solutions that improve the performance, availability and lifecycle value of Vanderlande’s automated logistics systems. The department designs, builds and operates scalable digital services that connect equipment, sites and operational data to cloud platforms for monitoring, analytics and optimization.

Working closely with engineering, service and product management teams, the department delivers capabilities such as predictive maintenance, operational insights, remote monitoring and AI-driven decision support. With multidisciplinary teams of software engineers, data scientists and domain experts, the department focuses on turning operational data from warehouses into actionable insights that reduce downtime, increase throughput and improve service efficiency.

Tasks/responsibilities

Expected activities:

• Data exploration: Analyze available datasets and understand their structure, relationships, and quality.
• Technology research: Investigate AI techniques for pattern discovery, anomaly detection, and Agentic AI.
• Pattern discovery: Identify correlations that can provide operational or service insights.
• Prototype development: Build a small proof-of-concept to demonstrate AI-generated insights.
• Evaluation: Assess feasibility, value, and potential integration into Vanderlande’s digital services.

Your profile

• Experience with Python, Java, Azure, or similar tools.
• Understanding pattern detection, clustering, anomaly detection.
• You are curious and enjoy experimenting to uncover hidden patterns.
• You are proactive.
• You can clearly document results and explain insights to both technical and non-technical audiences.

*Mandatory enrolment to a Dutch Education System & resident of The Netherlands