Vehicle noise testing & machine learning engineer

Are you passionate about automotive innovation, machine learning, and AI? Ready to apply your skills to real-world engineering challenges in a global company? Nissan is looking for a proactive and curious intern to join our NVH (Noise, Vibration & Harshness) Team.

• Support the development of a predictive model to better understand and estimate tyre noise based on key test parameters such as: Tyre pressure / stiffness / Vehicle speed / Ambient temperature / and other relevant vehicle and test conditions.
• To optimize the internal RAG application adding new technical parameters based on the history vehicle development key data.
• Analyse and process vehicle test data.
• Develop predictive models to estimate tyre noise behaviour.
• Investigate the influence of different tyre and vehicle parameters on exterior noise performance.
• Build an intuitive interface that enables engineers to simulate tyre noise based on different tyre specifications and operating conditions.
• Contribute to the digitalisation and optimisation of NVH engineering processes.

• Strong knowledge of Machine Learning and AI concepts and tools.
• Programming skills in Python or similar languages.
• Solid understanding of mathematical modelling and data analysis methods.
• Interest in applying technology to real engineering challenges.
• Fluency in English (spoken and written).
• You must be currently enrolled in a Bachelor's or Master's Degree and able to establish a university internship agreement with your academic institution.

• A hands-on internship with exposure to cutting-edge automotive technologies.
• The opportunity to work on a real project with direct impact on vehicle development.
• A multicultural and inclusive work environment with colleagues from around the world.
• Flexibility through hybrid working, combining remote work and collaboration at NTCE facilities.
• Financial compensation during the internship period.
• An excellent opportunity for students completing their Bachelor's Final Project or Master's Thesis.