Master thesis: Multimodal machine learning for anomaly detection in cloud operations

Lund, SE
den 26 november 2021
den 4 december 2021
Drift & System
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

In this master thesis project you will join us in our quest at crafting smart and efficient datacenters and cloud solutions. With the expected continued growth in the datacenter market, the cost of operating and running them need to be lowered. We anticipate that datacenters of tomorrow will be highly autonomous and require less on-site maintenance than today. Their energy efficiency can be improved on. To accomplish this the datacenters and cloud services must be instrumented and supervised to collect operational data and metrics. Then, this is fed into a powerful data analytics engine. Neural networks and reinforcement learning are key building block in this vision.

To be successful in the role you must have

The objective is to extend our current anomaly detection framework, which is based on log file data, to also consider metric data from the IT-equipment and facilities. This will require a machine learning approach that supports reasoning based on data of different categories, i.e., both text and values. We will be working with data from a real, large scale cloud service, as well as data from our virtual cloud lab. If successful, the applications will become an integral part of the Ericsson data-driven operations toolbox.

We expect the applicants to be familiar with various AI related concepts and technologies. Examples of these are supervised and unsupervised machine learning, classification and regression, reinforcement learning, and transfer learning. Most likely you are a final year master student, majoring in computer science, computer engineering, physics engineering, applied mathematics, or a similar topic.

What´s in it for you?

Here at Ericsson, our culture is built on over a century of fearless 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 chance to create an impact is endless.

What happens once you apply?

To prepare yourself for the next steps, please explore here:

Location for this role: Lund , Sweden

Recruiter: Srishti Tandon (

Last day to apply: 11th November 2021

Kindly note that we cannot process applications sent via email.

Ericsson provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to 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 genetics.

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.

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

Job details: Researcher Job Stage 04

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