Master Thesis: Analytic AI engine for Dynamic testing approach

We are now looking for master students within electrical, data or quality engineering that are interested in doing their thesis project at our Global SQA Electronics Department. Husqvarna is rapidly evolving in the field of product electrification. Traditionally known for mechanically robust and reliable products, we are now expanding our capabilities to meet the demands of modern, electrified solutions. This transformation brings new challenges and opportunities – not least in how we test and validate our electronic assemblies. As part of this shift, we recognize the need to improve and adapt our testing methodologies for PCBA (Printed Circuit Board Assemblies).For this we have an opening for a thesis work on master level. The aim of this thesis is to investigate methods including AI-tools for tailoring the scope of PCBA testing based on statistical data from previous test results.We want to combine the accumulated experience from past test results with the power of AI to implement a dynamic testing strategy – one that maintains high levels of quality assurance by identifying risk and value of each test.The objectiveThe purpose of this master's thesis is to analyze data from historical test results using AI-tools to assign value to each test effort. Based on this, the thesis will aim to identify potential areas for improvement and simplification within the testing procedure. The goal is to identify strategies and AI-tools that can increase the efficiency of testing while maintaining quality assurance.Proper area of educationMaster in Electrical, Data, Quality Engineering or similar,The thesis will include work such asCompilation and analysis of extensive test data. Identify trends, deviations, and quality indicators. This together with a study on the impact of quality when statistical data are affected. The study will deploy AI-based analytical frameworks to enhance the scope of the analysis. It will provide data-driven recommendations on how operational processes can be optimized through the integration of advanced machine learning and pattern recognition techniques.The work will be conducted in close collaboration with Supplier Quality Assurance department, R&D and external contacts at PCBA manufacturers, providing a broad perspective and valuable industry insights.The primary workplace is Husqvarna’s site in Huskvarna, with access to test systems, data sources, and engineering expertise.How to apply  Please send in your application with CV and cover letter no later than November 27th. Due to GDPR, we do not accept applications by email.Start date of the thesis project is in the spring term of 2026 or by agreement.For questions regarding the thesis project please contact:  Martin Lundström -martin.lundstrom@husqvarnagroup.com Read about Husqvarna Group here:  https://www.husqvarnagroup.com/   Husqvarna Group is a world-leading producer of outdoor power products for garden, park and forest care. Products include chainsaws, trimmers, robotic lawn mowers and ride-on lawn mowers. The Group is also the European leader in garden watering products and a world leader in cutting equipment and diamond tools for the construction and stone industries. The Group’s products and solutions are sold under the main brands Husqvarna & Gardena that serve professionals in more than 140 countries. The Group has around 14,000 employees in 40 countries.Last date to apply:06 October 2025