At Toyota Material Handling Europe (TMHE), we create the technology that keeps the world moving. Diverse businesses across Europe depend on our logistics and material handling solutions. By pioneering technology such as automation, connectivity and productivity solutions, we create opportunities for our customers’ logistics operations to be as efficient as possible.

We firmly believe in setting ideas in motion. That is why we are investing more than ever in research and development. Our multidisciplinary teams work both conceptually and practically to develop the next generation of material handling products and solutions. By providing our Research and Development organisation with the creative freedom and resources needed to explore new technologies, we aim to stay at the forefront of innovation. At Toyota Material Handling Europe, we contribute to a smarter and more sustainable society, today and tomorrow.

Background and purpose
Can machine learning help engineers estimate component costs more accurately and efficiently?

Cost estimation plays an important role in product development, influencing engineering, planning and sourcing decisions. Today, the process relies heavily on manual spreadsheets and expert knowledge, making it time-consuming and challenging to apply consistently.

At TMHE, we want to investigate whether historical product and cost data can provide a foundation for data-driven estimation. The purpose of this thesis is to evaluate the potential of machine learning to support cost estimation while maintaining transparency and engineering judgement.

Thesis description
Working with historical article and cost data, you will investigate how machine learning could support engineering cost estimation.

Your work will include:

• Analyse the available data and identify relevant cost drivers and potential limitations.
• Investigate and develop suitable machine learning approaches for cost prediction.
• Evaluate the results against existing estimation methods, considering accuracy and interpretability.
• Develop a proof of concept and recommend how the approach could support future engineering processes.

The outcome will provide an evidence-based assessment of the feasibility and potential value of machine learning for cost estimation.

We are looking for two Master’s students studying:

• Data Science or Machine Learning (ML)
• Computer Science or Artificial Intelligence (AI)
• Applied Mathematics or Statistics
• Industrial Engineering or a related field with relevant machine learning experience

You have a strong interest in applying data-driven methods to real engineering challenges and experience with programming for data analysis, preferably in Python. You approach problems analytically, enjoy experimenting with different solutions and can communicate technical findings clearly in English.

Beneficial skills (not mandatory)

• Experience with machine learning libraries such as scikit-learn.
• Familiarity with regression models, feature engineering or model evaluation.
• Knowledge of product development, manufacturing or engineering cost estimation.

At Toyota Material Handling Europe, you will work on a real engineering challenge and explore how machine learning could support future product development decisions.

You will be based at our Innovation Centre in Vallastaden, Linköping and the TMHE Headquarters in Mjölby, where you will receive guidance from experienced professionals and have opportunities to collaborate with engineers and other Master's students.

We believe in a flexible work environment that allows you to balance both your professional and personal life. At TMHE, you will have the opportunity to build valuable skills, contribute to impactful projects and be part of a collaborative, diverse and welcoming workplace. You will also receive competitive compensation in two instalments: one when you start your work and the other upon successful completion of your thesis.

Time for you to make a MOVE!

Your application
Please submit your application, including:

• A brief personal letter
• Your CV
• A recent transcript of records

For questions about the thesis, please contact your future mentor Simon Ekström at simon.ekstrom@toyota-industries.eu.

Applications are reviewed continuously, and suitable candidates may be invited to interviews before the deadline.

Terms

• Application: As soon as possible, or at the latest by the 30th of October 2026.
• Start date: During January 2027.
• Scope: 30 hp.
• Number of students: Two.
• Location: TMHE Innovation Centre, Vallastaden, Linköping (Main). You must be able to attend in-person meetings at our offices in Mjölby when required.