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Master Thesis: Resource Dimensioning Tool using Simulations and Machine Learning

Job Description

Date: Oct 18, 2019

Do you want to do your thesis with us in Karlskrona? 

Would you like the chance to do your thesis together with one of the world’s leading technology companies? We are on a quest to enable communication for everyone and everything and we believe that we do that by being as innovative as possible. If you want to help us to be even more innovative – then you are on the right track!


We want you to become a part of a truly global company working across borders in 180 countries, offering a diverse, performance-driven culture & an innovative & engaging environment where employees enhance their potential every day. Come and learn and grow with us at Ericsson!


Who we are?

As a master thesis worker, you will be a part of the SDI  - System Deployment and Infrastructure Team. We are responsible for architecting deployment strategies/visions and infrastructure issues. Looking ahead for how to implement and align Ericsson visions/technologies to the products. When necessary we do studies/proof of concepts of coming technologies.


The purpose of this thesis is to develop a tool for resource dimensioning of telecom systems using machine learning and simulation.

Thesis description:
Due to complexity of telecom systems the current resource dimensioning is not exact, while it does deliver a proposed infrastructure and use of resources as exact values. There is no possibility in the current dimensioning flow to assess the sensitivity to certain changes of dimensioning parameters and provide a result that results in a general statement that the infrastructure need is within certain +- values.

The current dimensioning process is cumbersome and requires dedicated and skilled resources and scenarios are not possible to create. As Infrastructure providers decided to move into a containerized setup, there are additional difficulties to be considered, e.g. more instances and smaller instances, internal POD signaling versus east-west signaling and general hardware requirements.


The purpose of this study is to analyze which tool set is to be used, where different DVs can be setup as state machines and allow a calculation and result using sensitivity analysis to provide a general view.


This project aims at students in telecommunication and networking engineering, computer science, data science, computer engineering or similar.

Background in signal processing is preferred.

Python, MATLAB/Simulink, Machine Learning and Data Analysis


All master program courses are preferably finished before start of thesis work.

Suitable for 1 student.



If you feel interested, please send in your application as soon as possible. The start date can be adjusted to both your and the business needs – the intention is to start in January/February 2020.

While applying please attach your updated CV, current grades and cover letter written in English into one document (under CV field in the application tool) and clearly define your technical knowledge.

For questions regarding the thesis, please contact Sogand Shirinbab (Supervisor) at or Elzbieta Penpeska (Recruiter) at


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Ericsson complies with applicable country, state and all local laws governing nondiscrimination in employment in every location across the world in which the company has facilities. In addition, Ericsson supports the UN Guiding Principles for Business and Human Rights and the United Nations Global Compact.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, training and development.

Ericsson expressly prohibits any form of workplace harassment based on race, color, religion, sex, sexual orientation, marital status, pregnancy, parental status, national origin, ethnic background, age, disability, political opinion, social status, veteran status, union membership or genetic information.


Primary country and city: Sweden (SE) || || Karlskrona || Stud&YP

Req ID: 302921