Master Thesis: AI-Driven RF Production Test Intelligence
Ericsson ABNy
Sammanfattning
This master thesis opportunity focuses on utilizing AI and machine learning to analyze large-scale RF production test data from Ericsson radio products. The role involves investigating various aspects of data-driven production intelligence, including anomaly detection, root cause analysis, and quality risk prediction. Located in Lund, Sweden, this position offers a chance to collaborate with supervisors to define research areas and develop actionable insights that enhance engineering processes.Det här erbjuder vi
Opportunity to work on cutting-edge AI and machine learning applications.Collaboration with a diverse team of innovators.Chance to contribute to solutions for complex engineering challenges.
Ansök senast: Öppet tillsvidare
Publicerad: 2026-10-06
Beskrivning
Join our Team
About this opportunity
This master-thesis will explore how AI and machine learning can transform large-scale RF production test data into actionable engineering insights. By correlating RF performance metrics with more factors, it aims to detect anomalies, support RCA, flag quality risks, and identify opportunities to optimize test coverage and time - helping engineers resolve issues faster and get higher quality products.
What you will do
This Master Thesis investigates the application of Artificial Intelligence and Machine Learning techniques on RF production test data from Ericsson radio products. You will have the opportunity to explore multiple aspects of data-driven production intelligence and define areas of focus together with supervisors.
Possible areas of investigation include, but are not limited to:
Production Data Understanding and Feature Engineering
Analyze large-scale RF production test datasets.
Identify key RF performance indicators and manufacturing parameters.
Develop methods for data cleansing, normalization, and feature extraction.
AI-Based Anomaly Detection
Investigate machine learning approaches for detecting abnormal test behavior.
Identify outlier devices and unusual production trends.
Compare conventional statistical methods with modern AI techniques.
Root Cause Analysis Support
Correlate RF test results with manufacturing information, component lots, test stations, environmental conditions, and other available factors.
Explore how AI can assist engineers in narrowing down potential root causes.
Develop explainable analysis methods to improve engineering confidence.
Production Quality Risk Prediction
Investigate predictive models for identifying potential quality risks before products leave manufacturing.
Study early indicators of future failures or yield degradation.
Evaluate model performance using historical production data.
Test Coverage Optimization
Analyze relationships between different production test steps.
Identify redundant measurements and opportunities to streamline testing.
Evaluate potential reductions in test time while maintaining product quality and fault coverage.
Data Visualization and Engineering Insights
Develop intuitive visualizations and dashboards for production data exploration.
Present AI-generated insights in a way that supports engineering decision-making.
Investigate techniques for explainable AI within a production environment.
Proof-of-Concept Implementation
Build and evaluate a proof-of-concept AI solution using real production data.
Demonstrate the ability to detect anomalies, provide engineering insights, and support production optimization activities.
Assess deployment opportunities and future industrial applications.
The skills you bring
Knowledge in Computer Science, Electrical Engineering, or a related field.
Knowledge of data visualization and statistical analysis.
Familiarity with RF systems, wireless communication, electronics, or manufacturing processes.
Experience in at least one programming language (Python not mandatory).
Eagerness to learn and explore new concepts.
Bonus: experience in machine learning.
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) || Lund
Req ID: 790711
About this opportunity
This master-thesis will explore how AI and machine learning can transform large-scale RF production test data into actionable engineering insights. By correlating RF performance metrics with more factors, it aims to detect anomalies, support RCA, flag quality risks, and identify opportunities to optimize test coverage and time - helping engineers resolve issues faster and get higher quality products.
What you will do
This Master Thesis investigates the application of Artificial Intelligence and Machine Learning techniques on RF production test data from Ericsson radio products. You will have the opportunity to explore multiple aspects of data-driven production intelligence and define areas of focus together with supervisors.
Possible areas of investigation include, but are not limited to:
Production Data Understanding and Feature Engineering
Analyze large-scale RF production test datasets.
Identify key RF performance indicators and manufacturing parameters.
Develop methods for data cleansing, normalization, and feature extraction.
AI-Based Anomaly Detection
Investigate machine learning approaches for detecting abnormal test behavior.
Identify outlier devices and unusual production trends.
Compare conventional statistical methods with modern AI techniques.
Root Cause Analysis Support
Correlate RF test results with manufacturing information, component lots, test stations, environmental conditions, and other available factors.
Explore how AI can assist engineers in narrowing down potential root causes.
Develop explainable analysis methods to improve engineering confidence.
Production Quality Risk Prediction
Investigate predictive models for identifying potential quality risks before products leave manufacturing.
Study early indicators of future failures or yield degradation.
Evaluate model performance using historical production data.
Test Coverage Optimization
Analyze relationships between different production test steps.
Identify redundant measurements and opportunities to streamline testing.
Evaluate potential reductions in test time while maintaining product quality and fault coverage.
Data Visualization and Engineering Insights
Develop intuitive visualizations and dashboards for production data exploration.
Present AI-generated insights in a way that supports engineering decision-making.
Investigate techniques for explainable AI within a production environment.
Proof-of-Concept Implementation
Build and evaluate a proof-of-concept AI solution using real production data.
Demonstrate the ability to detect anomalies, provide engineering insights, and support production optimization activities.
Assess deployment opportunities and future industrial applications.
The skills you bring
Knowledge in Computer Science, Electrical Engineering, or a related field.
Knowledge of data visualization and statistical analysis.
Familiarity with RF systems, wireless communication, electronics, or manufacturing processes.
Experience in at least one programming language (Python not mandatory).
Eagerness to learn and explore new concepts.
Bonus: experience in machine learning.
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) || Lund
Req ID: 790711
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Master Thesis: AI-Driven RF Production Test Intelligence
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Ericsson AB
