Master Thesis Project “AI Impact Severity Estimation”

Italdesign is an Italian design and engineering company specializing in automotive, transportation, and product development sectors.

Based in Moncalieri (Turin) with over 1,300 employees worldwide, it has been innovating and working with top car makers and emerging players for more than 57 years.

Renowned for its important role in car design, Italdesign has developed iconic vehicles and offers comprehensive services spanning exterior and interior design, prototyping, engineering, and turnkey project management. Its vertical integrated approach ensures seamless support to clients, from the first idea to homologation and series production, delivering solutions tailored to client needs.

Italdesign also develops new technologies and fosters advancements in mobility and prototyping. In recent years, it has expanded into electronic systems development, including infotainment, ADAS, high-voltage batteries, and Software Defined Vehicles (SDVs). This blend of technical expertise and creative design makes it a leader in the industry.

Since joining the Audi Group in 2010, Italdesign has grown and created innovative solutions, combining aesthetics and functionality to pioneer cutting-edge solutions that meet the market demands. In 2025 Italdesign obtained the Top Employers Certification for the tenth year in a row.

Italdesign is looking for an enthusiastic and smart student passionate about automotive, eager to join an innovative and international business environment, working in an agile way and embracing a strong team spirit.

You will gain a great experience in learning all the instruments, procedures and technical aspects with the support of your tutor and colleagues of the Department.

The objective of this thesis is to develop an algorithm based on Artificial Intelligence techniques capable of estimating the biomechanical injuries sustained by an individual following a road accident.

The research lies at the intersection of artificial intelligence, biomechanics, and elements of electronics applied to onboard automotive systems.

As thesis student, you will be supported by your Tutor in order to analyse and model data collected from in-vehicle information systems (e.g., sensors, telemetric data, kinematic and dynamic parameters of the event), integrated with biomechanical knowledge, to train deep learning and/or machine learning models able to accurately predict the extent of the injuries.

Specifically, you will perform the following activities:

• State-of-the-art assessment
• Design and implement a pipeline for data reading, preprocessing and model/s inference
• Predict Biomechanical damage on different body parts after a crash event

Key requirements

• Familiarity with Near-Real-Time inference speed;
• Academic knowledge of multi-head damage predictions for different body parts;
• Basic knowledge of trained model/algorithm;
• Academic knowledge of Python programming;
• Familiarity with Machine Learning libraries like Pytorch/Tensorflow/Transformers/Scikit-learn;
• Basic knowledge of Data Management with Python libraries like Pandas;
• Good team working skills;
• Responsibility and integrity;
• Good interpersonal and communicative skills;
• Good time management capability and proactivity;
• Good knowledge of Microsoft Office Package (Word, Excel, PowerPoint).

Preferential requirements

• Biomechanical basic knowledge;
• Time Series concepts.

Additional Information

Education: Attending a Master’s Degree in Data Science and Engineering, Computer Engineering, Mechatronic Engineering or Biomedical Engineering;

Language skills: Fluent knowledge of written and spoken Italian and English (at least B2 level);

Workplace: Moncalieri (TO) and Vadò (TO), Italy, with some visits to the Turin office;

Contract type: thesis project with estimated duration about 6 months and availability to start from February/March 2026;

Benefit: company canteen, multicultural environment.

Italdesign is committed to create an inclusive, diverse and safe workplace, and we are proud to be an equal opportunity employer (L.903/77).

We welcome applications from all candidates, regardless of the gender, ethnic, religion, sexual orientation, disability, parental status, or social origin.