Internship: Process Optimization using AI

Internship: Process Optimization using AI

Assignment type: Internship

Start date: June / September

Assignment duration: 4-6 months

Desired study: Mechanical Engineering, Industrial Engineering, Supply Chain Management, Econometrics or related studies

Language: Dutch/English

Description of assignment

Investigate the usage of AI in data analysis and process optimization, specifically within the simulation department, also focusing on power and energy sectors.

Department description

In the Simulation Department you will join a group of enthusiastic, highly trained young professionals. This team of simulation engineers conducts studies on the dynamic interaction in – and the logistics performance of – the complex material handling systems sold by Vanderlande. The team is involved in all the market segments and the large number of different processes within the Vanderlande organization, ranging from sales to service and from project execution to technology.

Tasks/responsibilities

• Analyze current processes and identify areas where AI can increase efficiency and speed of work.
• Implement AI tools to automate tasks, allowing the team to work more efficiently
• Collaborate with the team to enhance the quality and productivity of tasks through AI integration.
• Optimize simulation models
• Explore and improve functionalities of current tools for better data analysis and efficiency
• Implement and study the impact of new simulation features

Outcome: By the end of the internship, the intern will have helped streamline processes, increased productivity, and lowered the threshold for AI adoption within the department.

Your profile

• Excellent communication skills in both Dutch and English
• A proactive attitude
• Experience with Excel and a process/system way of thinking is a must.
• Python/Matlab is a plus.
• *Mandatory enrolment to a Dutch Education System & resident of The Netherlands.

“This internship offers a unique opportunity to work with cutting-edge AI technologies and make a tangible impact on our processes.” John Doe, Simulation Engineer