Master Thesis: Machine learning for 5G Core networks, automated network optimization

Job description

Job Description

Date: Nov 12, 2018

Description

The Research Area Machine Intelligence and Automation combines Machine Learning and Artificial Intelligence methods, tools, and techniques to create data driven, intelligent, sustanable systems for automation, augmentation, and amplification. The 5G program aims to define a new standard for Core Network (CN) with expanded service capabilities, scalability, agility and new core network functions across multi access technologies with unprecedented scale. It is Ericsson stearegy to evolve Macine Intelegent due to growing volumes and varieties of data, the utility of this data in training smart systems and an increased awareness of the value of data in providing a competitive edge in 5G enablers.

Machine intelligence is advanced computing that enables a machine to interact with its environment in an intelligent way combining both Artificial Intellegent and Machine Learning. We are looking for a talented student to work with us to apply Machine intelligence allowing our core network to operate more efficiently and effectively, using data to predict the future and manage the present. As a thesis worker, you will work on Mobility Management use cases from Core Network, run experiments on collected data to extract and classify data, detect and analyze and predict mobility patterns using Machine Learning such as Deep Learning. Some of these potential use cases is to improve amongst other paging and reduce signaling in the network, optimize network resources by planning handover based on analysis, etc.. In 5G, the deployment of smaller cells inevitably leads to more frequent paging/handovers, thus making mobility management more challenging and reducing the capacity gains offered by the network deployment. In order to fully reap the gains for mobile users in such a network environment, using intelligent mobility management through machine learning-based mobility prediction is essential. You will be able to evaluate different approaches for machine learning models to solve the problem specified in use cases. Besides optimize and automate processes for the selected approach. You will work together with an experienced research team from Ericsson and our partners in academia. The project will be performed in Kista and is expected to run in the spring 2019.

Qualifications

We are looking for a motivated individual with the following qualifications

·  Master’s student with most courses completed and good grades
·  Strong programming skills, specifically Python
·  Good knowledge of machine learning, statistics and packages such as Python, Tensorflow, Keras
·  Excellent communication and team working skills
·  Excellent written and spoken English, ability to work as part of an international team
·  Strong result orientation and thirst for knowledge

As the work is research oriented we expect an analytical mindset, ability to learn quickly, work independently and being able to identify problems and solutions.

Applications should include a short motivation letter, CV, and transcripts of records. Candidates are invited to send their applications as soon as possible.

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

Req ID: 262604