Master thesis in scaling and leveraging ai and generative ai for production lines

Background:

Scania is currently undergoing an exciting transformation from a traditional truck manufacturer to a provider of complete sustainable transport solutions. If you're seeking a dynamic work environment for your thesis, Scania Production System focuses on continuous improvements to enhance the efficiency and effectiveness of its production processes. With the rise of automation, digitalization, and the smart factory concept, we are now at the forefront of the fourth industrial revolution.

The Smart Factory Lab at Scania is an experimental test environment that explores, assesses, and pilots new technologies before they are adopted in Scania’s production processes. The lab focuses on digitalization and automation with the target of achieving autonomous material handling, reduction of quality deviations, and shortened introduction time. This will increase safety, productivity, quality, and human well-being. We are looking for motivated and creative students to join our Smart Factory Lab for their master thesis. The thesis will involve working on innovative projects that explore how emerging technologies can enhance our production, engineering, and collaboration processes. You will have the opportunity to work in a dynamic and collaborative environment, where you can test and validate new technologies, methods, and solutions in close collaboration with our internal and external stakeholders

Assignment:

The data driven team at Smart Factory Lab keeps exploring the new cutting-edge technologies and tools in data and AI. There are multiple exciting use cases in the field of AI, Generative AI (GenAI) and Computer Vision where we want to support people in Production and Logistics to improve safety, quality, delivery, cost and efficiency.

Key questions:

How can cloud-based MLOps tools (e.g. Databricks) be leveraged to automate the maintenance and scaling of AI models in production lines?
How can large language models (LLMs) combined with computer vision, be used to enable operators to receive task validation and feedback?
How can text-to-code LLMs, specifically for SQL and Python, automate data analysis, educate users, and accelerate development through real-time code generation?
Education and time plan

Education:

Master’s program in Computer Science, Automation Engineering, Data Science, Artificial Intelligence , Machine or Cloud Computing

Number of students: 1-2
Start date: January 2025
Estimated time needed: 20 weeks

Contact persons and supervisors
David Svensson, Manager, david.svensson@scania.com, tel. +46700863673

Application:
Your application must include a CV, personal letter and transcript of grades.

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified