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Master Thesis: Modelling RAN Features with KN Graphs at Ericsson

Stockholm, , Sweden -

Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

0.0

Posted On

23 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Modelling, Algorithms, Graph Theory, Probability, Statistics, Formal Methods, Graph Databases, Neo4j, Cypher, RDF, SPARQL, RAN Concepts

Industry

Telecommunications

Description

Enrolment in a master's program (Computer Science, Electrical Engineering, Applied Mathematics, or related field). Strong background in modelling, algorithms, graph theory, probability/statistics, or formal methods. Experience with graph databases (Neo4j/Cypher, RDF/SPARQL) or willingness to learn quickly. Familiarity with RAN concepts is a plus; domain training will be provided. If you want to contribute to shaping more reliable and explainable network intelligence in next-generation networks and enjoy translating complex RAN interactions into structured, queryable knowledge, this thesis opportunity is for you. 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. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. learn more. Primary country and city: Sweden (SE) || Stockholm Req ID: 775312

Responsibilities

The thesis opportunity involves modelling RAN features using KN graphs. The candidate will contribute to shaping reliable and explainable network intelligence in next-generation networks.