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Master thesis project

Braga
Continental
Projectista
Anunciada dia 24 outubro
Descrição

Job Description

Can you imagine why it is important for a Tire manufacturer to know the expected mileage of their tires?

Although state-of-the-art methods and techniques to theoretically estimate these values based on the tire's characteristics do exist their performance in the field it is highly influenced by many more factors such as the application as well as the geography they are used for, their position within the vehicle, the skills of the driver and many more.

To verify what is their field wear performance, to benchmark new tires recipes against old or competitor's equivalent tires and early detect potential defects during development, several Field Tests are commissioned each year to Global Tire Testing. As you can imagine these tests are expensive and could only be a subset of all the "wished" tests. Nevertheless, due to their importance they are performed, and they are a rich source of data which currently supply the right answer only to whoever is commissioning the test.

The aim of this initiative is to unleash the power of this Tabular data with the help of Large Language Models (LLMs) together with traditional Machine Learning approaches to be able to generalize to contractual configurations not contained in the historical data and be able to provide a reliable KPIs for new tire products, vehicles, customers, and regions.

Besides tire testing, also complaints prediction, compound recipe generation and product portfolio consolidation could benefit from the approach.

Qualifications

1. Training Area in Computer Science, Artificial Intelligence, Data Science or similar;
2. Good knowledge of Python (pandas, scikitlearn, numpy) and Linux;
3. Basic knowledge of some AWS services (EC2, S3 buckets);
4. Basic knowledge on data engineering;
5. Basic understanding of code versioning ( Git);
6. Basic knowledge on Machine Learning;
7. Airflow is a plus.

Additional Information

Our offer:

8. Integration in a challenging and international work environment;
9. Collaborative working style;
10. Learning opportunities for professional development.

We are committed to fostering a workplace where everyone feels safe, respected, and valued. All kind of applications are welcome.

Please note:

11. Mandatory to be studying in a Portuguese University, ready to start Master Thesis Project.
12. To initiate on the 2nd Semester of 2025-2026.

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