MSc thesis: Advanced ML for prediction of network and service performance in dynamic environments

Stockholm, SE
den 20 oktober 2021
den 11 november 2021
As the tech firm that created the mobile world, and with more than 54,000 patents to our name, we've made it our business to make a mark. When joining our team at Ericsson you are empowered to learn, lead and perform at your best, shaping the future of technology. This is a place where you're welcomed as your own perfectly unique self, and celebrated for the skills, talent, and perspective you bring to the team. Are you in?

Come, and be where it begins.

Our Exciting Opportunity

Do you want to take part in the AI journey towards 6G? It has already started!

We at Ericsson Research, Research Area Artificial Intelligence, are looking for a talented student to work with us in the international research project ANIARA ( ), where researchers from Ericsson collaborate with industrial and academic peers across Europe on network automation and optimization for 5G and 6G edge networks.

In this project you will work with us on state-of-the-art AI/ML and advanced data science techniques to enhance existing solutions with specific focus on model reusability and improved learning efficiency using approaches from the fields of transfer learning and domain adaptation. Requirements on model reusability originates from the highly dynamic and flexible environment of the future intelligent network platform. Specifically, you will develop and evaluate state-of-the-art ML models based on transfer learning and/or domain adaptation techniques with the aim of reducing training time, energy consumption, and improving the performance by leveraging on previously acquired insights.

To be successful in the role you must have

  • 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/Scikit-learn, PyTorch, Tensorflow, and Keras
  • Good knowledge of and interest in mathematics and statistics
  • Good knowledge of computer networks, cloud and virtualization
  • Excellent written and spoken English

What´s in it for you?

Here at Ericsson, our culture is built on over a century of courageous decisions. With us, you will no longer be dreaming of what the future holds - you will be redefining it. You won't develop for the status quo, but will build what replaces it. Joining us is a way to move your career in any direction you want; with hundreds of career opportunities in locations all over the world, in a place where co-creation and collaboration are embedded into the walls. You will find yourself in a speak-up environment where empathy and humanness serve as cornerstones for how we work, and where work-life balance is a priority. Welcome to an inclusive, global company where your opportunity to make an impact is endless.

What happens once you apply?

To prepare yourself for next steps, please explore here:

Hiring manager: In this role you will report to Master Researcher

Recruiter: Karolina Jałkowska (

Location: Stockholm, Sweden

Kindly note that we do not accept applications sent via e-mail

Do you believe that an organization fostering an environment of cooperation and collaboration to execute with speed creates better business value? Do you value a culture of humanness, where fact based decisions are important and our people are encouraged to speak up? Do you believe that diverse, inclusive teams drive performance and innovation? At Ericsson, we do.

We provide equal employment opportunities without regard to race, color, gender, sexual orientation, transgender status, gender identity and/or expression, marital status, pregnancy, parental status, religion, political opinion, nationality, ethnic background, social origin, social status, indigenous status, disability, age, union membership or employee representation and any other characteristic protected by local law or Ericsson's Code of Business Ethics.

Primary country and city: Sweden (SE) || || Stockholm || [[mfield2]]

Req ID: 595809

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