Master Thesis: Discovering Building Blocks in Test Environments
Confirmed on the employer's own hiring board on Oct 23, 2026. First seen by Alion on Oct 21, 2026. Ericsson scores B on the Alion truth index.
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About this opportunity
Are you a Master’s student interested in Python, graph algorithms, data analysis or machine learning? Would you like to explore how data can be used to identify patterns and improve the way complex telecom test environments are understood and managed?
Radio network software is tested in physical environments consisting of real base station hardware, radios, network equipment and simulators. To make these environments easier to build and use, equipment can be organized into predefined Building Blocks, where equipment is connected in a standardized way to provide a specific capability.
However, today it can be difficult to get a complete picture of these Building Blocks. How many instances exist? Where does a Building Block almost exist, perhaps with only one connection missing? And are there recurring equipment structures that could become new Building Blocks?
In this Master’s thesis, you will explore how existing test environment data can be transformed into a living inventory of Building Blocks. You will investigate graph-based methods and potentially machine learning to identify existing, near-matching and previously undeclared structures in real data.
The project will be held in our Ericsson office in Linköping, with preferred start in January 2027.
What you will do
- Explore graph pattern matching and data mining methods relevant to the problem.
- Develop a prototype that identifies Building Blocks and near-matches in test environment data.
- Investigate whether recurring structures can be discovered using graph mining or machine learning.
- Evaluate the solution using representative test environment data.
- Present your prototype, findings and recommendations to the Ericsson team.
The exact technical direction and implementation can be further shaped together with your Ericsson supervisors as the thesis progresses.
The skills you bring
We believe you are currently studying a Master’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
For this thesis, we are especially interested in students who:
- Have experience working with Python.
- Have an interest in algorithms, data analysis and software development.
- Are curious about graph algorithms, data mining and applied machine learning.
- Enjoy working with complex datasets and turning them into practical solutions.
- Have an analytical and problem-solving mindset.
- Are motivated to explore different approaches and build a working prototype.
Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you apply?Click Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: Sweden (SE) || Linköping
Req ID: 793190