Vehicle Noise Testing & Machine Learning Engineer, Trainee

Nissan Motor Co., Ltd.; Barcelona; Hybrid; EUR 6,700 - 10,000; Part time

Benefits offered by this job

Financial compensation

Hybrid work setup

Hands-on internship

Job summary

Nissan Motor Co., Ltd. in Barcelona invites an intern to join the NVH team as Vehicle Noise Testing & Machine Learning Engineer, Trainee. You will support predictive modelling to estimate tyre noise from key test parameters, using Python and ML tools while contributing to digitalising NVH processes.

The role offers a hands-on experience with automotive tech, a real project with global impact, and a hybrid work setup with access to NTCE facilities, ideal for students completing final projects.

Qualifications

• Must be enrolled in a Bachelor's or Master's degree and able to arrange university internship agreement.
• Strong knowledge of ML/AI concepts and tools.
• Programming skills in Python or similar languages.

Responsibilities

• Analyze and process vehicle-related test data.
• Develop predictive models to estimate tyre noise based on test parameters.
• Investigate influence of tyre and vehicle parameters on exterior noise.
• Build an intuitive interface to simulate tyre noise under different specs and conditions.
• Contribute to digitalisation and optimisation of NVH engineering processes.

Skills

Machine Learning

Python

Data analysis

English

Education

Bachelor's or Master's student

Tools

Pandas

Scikit-learn

Job description

Vehicle Noise Testing & Machine Learning Engineer, Trainee

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.

Your Mission

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.

Using Machine Learning and AI tools, your goal will be to:

• 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.

We're Looking For a Motivated Candidate With:

• 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).

What We Offer

• 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.

To join this internship experience, 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.

At Nissan, we believe that the differences among us – differences in race, gender, age, mindset, religion, people with disabilities and much more – make us stronger and equip us to better serve our customers and communities. We are committed to creating positive change that ensures transparency and inclusivity throughout the career journey, in order to build teams that create a sense of belonging for all members.

Barcelona Barcelona Spain