About this opportunity:
 

This thesis focuses on using Machine Learning (ML) and Artificial Intelligence (AI) techniques to classify residential areas based on time-series data from radio access networks. The objective is to group areas (dense urban, urban, suburban, and rural) according to network demands, contributing to network planning and optimization. This project addresses the challenge of missing geolocation data by providing data-driven insights into network capacity and coverage needs, influencing future product and feature design. 

 

​What you will do: 
 

Conduct a literature review on Radio Access Networks (RAN) and ML/AI methods for classification. 

Analyze and process time-series data to extract relevant patterns and features for classification. 

Develop and implement ML/AI models to classify residential areas based on their network needs. 

Validate models across different regions and assess their applicability in various environments. 
 

The skills you bring:

Data Analysis and Preprocessing: Experience with analyzing and preparing time-series data, feature extraction, and transformation techniques. 

ML/AI Knowledge: Strong understanding of machine learning and AI techniques used for classification tasks. 

Programming: Proficiency in Python for developing ML/AI models, data processing, and evaluation. 

Problem-Solving: Ability to extract meaningful insights from time-series data and apply these to real-world network classification problems. 

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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: 757477