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Master Thesis: Automated alignment of telecom site DTs and city-scale maps

Technology, Data & Digital · Software & Web Development · Software Engineering · Data Science

In short

Master Thesis project focused on developing automated methods to align detailed telecom Site Digital Twins (from UAV/LiDAR, NeRF, BIM) with city-scale 2.5D/3D maps (USDC, glTF, Mitsuba XML). The role involves implementing and testing alignment pipelines using computer vision, 3D geometry, and machine learning techniques, measuring results, and extending existing Ericsson solutions.

Responsibilities

  • Develop and evaluate automated methods to align detailed telecom Site Digital Twins with city-scale 2.5D/3D maps.
  • Work across different representations, such as UAV- or LiDAR-derived point clouds, NeRF models and BIM, and city-scale maps in formats such as USDC, glTF and Mitsuba XML.
  • Investigate geometric and spatial discrepancies between the detailed site models and the broader map context, and develop approaches to improve alignment and consistency.
  • Implement and test alignment or registration pipelines, using suitable computer-vision, 3D-geometry and machine-learning techniques.
  • Measure the quality and robustness of your approach, analyse failure cases and document findings relevant to radio-propagation modelling and Network Digital Twins.
  • Extend existing Ericsson solutions and present your results and recommendations to the research team.

Requirements

  • Pursuing a Master’s degree (or equivalent) in computer science, electrical engineering, robotics, computer vision, geomatics or a related field, and are looking for a thesis project.
  • Comfortable programming in Python and at least one additional language, such as C++, JavaScript or another relevant language.
  • Ability to reason about 3D geometry and spatial data, evaluate technical results and communicate your approach clearly.
  • Thoughtful use of modern AI-assisted research and programming tools, with the ability to independently understand, debug, validate and take ownership of your code.

Desired Qualifications

  • Experience with point-cloud registration, coordinate systems, UAV/LiDAR data, city-map formats or digital twins is an advantage.
  • Familiarity with at least one relevant area, such as 3D computer vision, point clouds, 3D graphics or modelling, rendering, photogrammetry, BIM or NeRFs is an advantage.

Benefits

  • Outstanding opportunity to use your skills and imagination to push the boundaries of what’s possible.
  • Chance to build solutions never seen before to some of the world’s toughest problems.
  • Be challenged, but not alone; join a team of diverse innovators.
  • Opportunity to go beyond the status quo to craft what comes next.

Skills

PythonC++JavaScriptpoint-cloud registrationcoordinate systemsUAV/LiDAR datacity-map formatsdigital twins3D computer visionpoint clouds3D graphicsmodellingrenderingphotogrammetryBIMNeRF
#thesis#master thesis#automated alignment#telecom#digital twins#city-scale maps#UAV#LiDAR#pointclouds#NeRF#BIM#USDC#glTF#Mitsuba XML#computer vision#3D geometry#machine learning#radio propagation modelling#network digital twins
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Company

Ericsson

Job Posted

1 day ago

Employment Type

Internship

Work mode

On Site

Experience Level

Entry

Locations

Stockholm, Sweden

Qualification

Master

Applicants

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