Master Thesis: AI-Assisted Root Cause Analysis for Cloud RAN
Ericsson ABNy
Sammanfattning
This thesis opportunity focuses on developing an AI-assisted investigation framework for Cloud RAN Layer 1 at Ericsson in Stockholm, Sweden. The role involves analyzing Trouble Reports to identify affected subsystems, retrieve historical cases, generate hypotheses, and recommend investigation steps using advanced AI technologies. Candidates will work independently while collaborating with a diverse team of innovators in a challenging environment.Det här erbjuder vi
Opportunity to work on cutting-edge AI technologies.Collaborative and diverse work environment.Chance to tackle complex problems in telecommunications.
Ansök senast: Öppet tillsvidare
Publicerad: 2026-09-29
Beskrivning
Join our Team
About this opportunity:
Artificial Intelligence is transforming how software is developed, tested, and maintained. At the same time, modern mobile networks are becoming increasingly complex, generating large amounts of engineering data from customer deployments, verification activities, simulations, and software development processes.
Cloud RAN Layer 1 (CR L1) is one of the most performance-critical software domains within Ericsson's Radio Access Network portfolio. When a problem is discovered, engineers often need to analyze Trouble Reports (TRs), logs, traces, simulation results, software changes, and technical documentation to identify the root cause.
This investigation process can be time-consuming and heavily dependent on expert knowledge.
The objective of this thesis is to explore how modern AI technologies can assist engineers by finding relevant historical cases, identifying likely affected subsystems, and recommending investigation paths for new Trouble Reports.
What you will do:
The objective of this thesis is to design, implement, and evaluate an AI-assisted investigation framework for Cloud RAN Layer 1.
The proposed solution should be capable of:
• Analyzing new Trouble Reports
• Identifying likely affected software subsystems
• Retrieving similar historical Trouble Reports and fixes
• Generating root-cause hypotheses
• Recommending investigation steps
• Presenting supporting evidence for its conclusions
Depending on the selected approach, the work may involve technologies such as:
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Semantic Search
• Knowledge Graphs
• Machine Learning and Data Analytics
The skills you bring:
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) || Stockholm
Req ID: 791748
About this opportunity:
Artificial Intelligence is transforming how software is developed, tested, and maintained. At the same time, modern mobile networks are becoming increasingly complex, generating large amounts of engineering data from customer deployments, verification activities, simulations, and software development processes.
Cloud RAN Layer 1 (CR L1) is one of the most performance-critical software domains within Ericsson's Radio Access Network portfolio. When a problem is discovered, engineers often need to analyze Trouble Reports (TRs), logs, traces, simulation results, software changes, and technical documentation to identify the root cause.
This investigation process can be time-consuming and heavily dependent on expert knowledge.
The objective of this thesis is to explore how modern AI technologies can assist engineers by finding relevant historical cases, identifying likely affected subsystems, and recommending investigation paths for new Trouble Reports.
What you will do:
The objective of this thesis is to design, implement, and evaluate an AI-assisted investigation framework for Cloud RAN Layer 1.
The proposed solution should be capable of:
• Analyzing new Trouble Reports
• Identifying likely affected software subsystems
• Retrieving similar historical Trouble Reports and fixes
• Generating root-cause hypotheses
• Recommending investigation steps
• Presenting supporting evidence for its conclusions
Depending on the selected approach, the work may involve technologies such as:
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Semantic Search
• Knowledge Graphs
• Machine Learning and Data Analytics
The skills you bring:
- MSc student in Computer Science, Artificial Intelligence, Software Engineering, Data Science, Electrical Engineering, Telecommunications, or similar
- Proficiency in Python and C++
- Strong analytical and problem-solving skills
- Experience with vector databases, knowledge graphs, or AI agents
- Knowledge of Retrieval-Augmented Generation (RAG), semantic search, or information retrieval
- Knowledge of wireless communications, 5G, or telecommunications systems
- Ability to work independently and communicate technical findings effectively
- Good written and spoken English.
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) || Stockholm
Req ID: 791748
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Master Thesis: AI-Assisted Root Cause Analysis for Cloud RAN
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Ericsson AB
