Master Thesis: Anomaly Detection in Telecommunications Logs Using Energy-Efficient AI

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About the opportunity
Ericsson is a world-leading provider of telecommunications equipment and services, supporting mobile and fixed networks in more than 180 countries. Our global, innovative, and collaborative environment gives employees and students the opportunity to work on challenging problems that shape the future of communication networks. As next-generation networks generate an increasing volume of system logs, manual monitoring is no longer feasible. Although deep-learning methods can detect anomalies with high precision, they may also require substantial computational resources and energy.

In this thesis, you will investigate AI-based anomaly-detection methods for telecommunications logs, with a focus on reducing energy consumption without compromising detection performance. By exploring lightweight architectures and energy-aware optimisation techniques, the project aims to contribute to more efficient network operations.

The thesis is intended for one student. The scope may be adapted to align with the candidate's research interests and background.

What you will do
During the thesis, you will:

• Conduct a literature review of relevant concepts and algorithms for anomaly detection in telecommunications logs.
• Investigate and test suitable machine-learning and AI algorithms.
• Select and implement appropriate techniques for different scenarios within the chosen use case.
• Develop an end-to-end prototype or proof of concept.
• Evaluate the resulting model in terms of detection performance, computational requirements, and energy efficiency.
• Analyse the results and identify opportunities for further improvement.

The skills you bring
We are looking for a highly motivated student who enjoys challenging research work and is eager to propose and develop new ideas.

You have:

• An MSc background in Computer Science, Mathematics, Physics, Engineering, or a related field.
• Excellent programming skills in Python.
• Good knowledge of machine learning, including deep learning, unsupervised learning, and anomaly detection.
• Experience with machine-learning libraries and frameworks such as TensorFlow, Keras, PyTorch, Scikit-Learn, or Spark.
• An interest in building end-to-end prototypes and developing practical concepts.
• The ability to work independently while collaborating effectively with others.
• Fluency in English.

Knowledge of Docker containers, orchestration systems, and telecommunications is considered an advantage.

When applying, please include a transcript of records showing your completed courses and grades.

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) || Luleå

Req ID: 791566