Graduation: Integrating Component Simulations in Digital Twins with Machine Learning
- Machine learning
- Other places
- 07/01/2024
- -
Assignment type: Graduation
Start date: September 2024
Assignment Duration: 9 months
Location: Veghel
Educational Level: WO (MSc)
Desired Study: Computer Science, Mathematics, any technical study with programming affinity
Language: Dutch / English
At Vanderlande, we utilize various simulation models for unique use cases. While component simulation models offer high detail and accuracy, their complexity makes it impractical to incorporate them into large-scale systems due to excessive computational requirements. Developing simpler component models demands significant effort and expert knowledge, often compromising accuracy. Additionally, maintaining alignment between detailed and simple models throughout a product’s lifecycle presents further challenges. Therefore, we aim to explore an alternative approach. In this graduation assignment, you will employ machine learning techniques to train a simplified component model using data from the detailed component model for effective system simulation integration.
The Digital Twin Suite team develops software for configuring system-level Digital Twins utilized in simulation and emulation. Our Simulation team customizes these platforms for project-specific models to analyze and optimize system performance.
Do you resonate with this challenging profile? Are you seeking an internship within our organization? Please complete the application form and upload your resume and cover letter. For more information, reach out to us via email at or contact Klejdi Filaj (Campus Recruiter) by phone: +31 4 134 946 51.
Company Name: Vanderlande
Job Title: Graduation: Integrating Component Simulations in Digital Twins with Machine Learning