Master Thesis: AI-assisted Early Analysis of Power-Saving Features on Ericsson Radios

## Join our Team # About this opportunity How can artificial intelligence help us build more energy-efficient mobile networks? Reducing energy consumption is one of the most important challenges in modern telecommunications. Ericsson continuously develops power-saving features that enable 4G and 5G networks to reduce energy usage while maintaining high performance. As the number and complexity of these features increase, understanding their behavior and identifying potential issues early becomes increasingly challenging. In this thesis, you will explore how Large Language Models (LLMs) and AI techniques can be used to understand, recognize, and analyze power-saving features in Ericsson radios. By combining knowledge of radio systems, Energy Performance features, and AI, you will investigate how early assessments can be automated and enhanced. The results can help engineers identify problems sooner, accelerate feature development, and contribute to more sustainable mobile networks with lower environmental impact. What you will do You will study Energy Performance and power-saving features used in Ericsson radios and investigate how AI can support their analysis. The work will focus on developing concepts and methods that enable earlier understanding of radio behavior and faster identification of potential issues. You will have freedom to define areas of exploration within the project. These could include, but are not limited to: * Understanding the fundamentals of Energy Performance and power-saving features in 4G and 5G networks. * Investigating how radio behavior reflects the operation of different power-saving features. * Exploring how Large Language Models and other AI techniques can be applied to engineering analysis. * Developing methods to train or guide AI models to recognize and reason about multiple power-saving features. * Analyzing radio data and feature behavior to identify anomalies or potential issues at an early stage. * Evaluating how AI-assisted analysis can improve current ways of working. * Proposing new workflows and methodologies that leverage AI to accelerate Energy Performance feature assessment and development. The skills you bring * Knowledge in Computer Science, Electrical Engineering, Telecommunications, Data Science, or a related field. * Experience in at least one programming language. * Interest in artificial intelligence, machine learning, and data analysis. * Curiosity about wireless communication systems and sustainable technology. * Eagerness to learn how modern mobile networks can reduce energy consumption while maintaining performance. * Bonus: knowledge of 4G/5G systems, Large Language Models, machine learning, data analytics, or software development.