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Assignment type: Graduation
Start date: September 2025
Assignment Duration: 6 – 9 months
Educational Level: Master
Desired Study: Computer Science, Mathematics or any technical study with programming affinity
Language: Dutch / English
Assignment
Vanderlande uses different simulation models for different use cases. Component simulation models are highly detailed and accurate, however this level of detail makes it infeasible to integrate into large scale systems simulation, as this would become too computationally expensive and slow to be useful. Developing simpler component models requires significant effort as well as expert knowledge of component behaviour, and typically results in a model with lower accuracy. Additionally, it poses the challenge of keeping the detailed and simple models aligned over the life cycle of a product. Because of these downsides we want to investigate a different option. In this graduation assignment we want to use machine learning techniques to train a simple component model for use in system simulations, using training data from the detailed component model.
Department
The Digital Twin Suite develops the software platform used to configure system-level Digital Twins for simulation and emulation purposes. The Simulation team uses this simulation platform to configure project-specific simulation models, which they use to analyse and optimize system performance.
Tasks/responsibilities
Skills / Your profile
Contact
Do you recognize yourself in this challenging profile? Are you looking for an internship in our organization? For more information, contact us by e-mail: internship@vanderlande.com
Vanderlande is the global market leader for value-added logistic process automation at airports, and in the parcel market. Vanderlande’s baggage handling systems move 4.2 billion pieces of luggage around the world per year. Its systems are active in 600 airports including 14 of the world’s top 20.
Resources:
Change language to: English
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