Master Thesis: Strategic Research Taxonomy Generation and Knowledge Discovery
Ericsson ABNy
Sammanfattning
Ericsson Research is seeking a Master's student for a thesis project focused on improving research discoverability through the development of a data-driven taxonomy. The role involves reviewing existing taxonomies, investigating research artefacts, and creating methods for integrating predefined research areas with automatically generated subdomains. This position is based in Stockholm, Sweden, and offers the opportunity to contribute to innovative knowledge management solutions within a diverseDet här erbjuder vi
Opportunity to work on innovative solutions in a collaborative environment.Engagement with a diverse team of innovators.Support for personal and professional growth within the organization.
Ansök senast: Öppet tillsvidare
Publicerad: 2026-09-30
Beskrivning
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About this opportunity:
Ericsson Research generates a vast amount of technical knowledge through reports, publications, patents, studies, prototypes, presentations, and other research artefacts. As the volume of information grows, it becomes increasingly difficult to organize and navigate this knowledge in a structured manner.
Recent work within Ericsson Research has demonstrated the feasibility of automatically generating research taxonomies from internal research artefacts. While these approaches can identify relationships between topics and uncover emerging research themes, that do not necessarily align with the strategic research areas and terminology commonly used within Ericsson Research. Manually maintained taxonomies, meanwhile, can struggle to keep pace with rapidly evolving research fields.
This thesis will investigate how organisational knowledge structures can be combined with data-driven taxonomy generation to improve research discoverability, support strategic decision-making, reveal relationships between research areas, and help researchers identify relevant knowledge beyond their immediate field of expertise.
The objective is to design and evaluate methods for generating and maintaining a research taxonomy that combines predefined organisational research domains with automatically discovered subdomains and topic structures extracted from Ericsson Research artefacts. The work will also support the discovery of adjacent fields, emerging topics, knowledge gaps, and alignment between strategic domains and observed research output.
What you will do:
Review research on taxonomy generation, ontology learning, topic modelling, knowledge graphs, scientific knowledge organisation, and research mapping.
Investigate existing Ericsson Research taxonomies, strategic research-area definitions, research artefacts, and previous work on automatic taxonomy generation and topic discovery.
Develop or adapt methods for incorporating predefined top-level research areas into a data-driven taxonomy-generation process.
Develop techniques for identifying subfields, relationships and overlaps between fields, emerging and interdisciplinary topics, and gaps between expected and observed research activity.
Evaluate the generated taxonomy using quantitative and qualitative methods.
Develop a prototype and demonstrate how the taxonomy can be integrated into Ericsson Research Insight Exploration to support navigation, discovery, and exploration of research knowledge.
Analyse the results and provide recommendations for long-term taxonomy management, knowledge discovery, and future integration.
Present the findings, evaluation results
The skills you bring:
You are pursuing a Master's degree in Computer Science, Machine Learning, Data Science, Information Retrieval, Knowledge Engineering, Human-Computer Interaction, or a related field.
You have strong analytical, research, problem-solving, and communication skills.
You are interested in organisational knowledge management, research mapping, information retrieval, or AI-supported knowledge discovery.
You have programming experience in Python and an ability to work independently with an open research question.
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: 790984
About this opportunity:
Ericsson Research generates a vast amount of technical knowledge through reports, publications, patents, studies, prototypes, presentations, and other research artefacts. As the volume of information grows, it becomes increasingly difficult to organize and navigate this knowledge in a structured manner.
Recent work within Ericsson Research has demonstrated the feasibility of automatically generating research taxonomies from internal research artefacts. While these approaches can identify relationships between topics and uncover emerging research themes, that do not necessarily align with the strategic research areas and terminology commonly used within Ericsson Research. Manually maintained taxonomies, meanwhile, can struggle to keep pace with rapidly evolving research fields.
This thesis will investigate how organisational knowledge structures can be combined with data-driven taxonomy generation to improve research discoverability, support strategic decision-making, reveal relationships between research areas, and help researchers identify relevant knowledge beyond their immediate field of expertise.
The objective is to design and evaluate methods for generating and maintaining a research taxonomy that combines predefined organisational research domains with automatically discovered subdomains and topic structures extracted from Ericsson Research artefacts. The work will also support the discovery of adjacent fields, emerging topics, knowledge gaps, and alignment between strategic domains and observed research output.
What you will do:
Review research on taxonomy generation, ontology learning, topic modelling, knowledge graphs, scientific knowledge organisation, and research mapping.
Investigate existing Ericsson Research taxonomies, strategic research-area definitions, research artefacts, and previous work on automatic taxonomy generation and topic discovery.
Develop or adapt methods for incorporating predefined top-level research areas into a data-driven taxonomy-generation process.
Develop techniques for identifying subfields, relationships and overlaps between fields, emerging and interdisciplinary topics, and gaps between expected and observed research activity.
Evaluate the generated taxonomy using quantitative and qualitative methods.
Develop a prototype and demonstrate how the taxonomy can be integrated into Ericsson Research Insight Exploration to support navigation, discovery, and exploration of research knowledge.
Analyse the results and provide recommendations for long-term taxonomy management, knowledge discovery, and future integration.
Present the findings, evaluation results
The skills you bring:
You are pursuing a Master's degree in Computer Science, Machine Learning, Data Science, Information Retrieval, Knowledge Engineering, Human-Computer Interaction, or a related field.
You have strong analytical, research, problem-solving, and communication skills.
You are interested in organisational knowledge management, research mapping, information retrieval, or AI-supported knowledge discovery.
You have programming experience in Python and an ability to work independently with an open research question.
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: 790984
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Master Thesis: Strategic Research Taxonomy Generation and Knowledge Discovery
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OM FÖRETAGET
Ericsson AB
