Ericsson Master thesis: 5G - ML based Human Instructor feedback system using Haptic + visual signals

Posted date: Jan 12, 2021

Location: Stockholm, AB, SE

Company: Ericsson

Thesis background

There are different types of sensors that can capture the motions of objects. Among which are Haptic sensors that can create a 3D sense of touch and to add realtime feedback to the users. The industry application ranges from healthcare, E-commerce, robotics, game and entertainments. The most known Haptics example is the vibration in the mobile phones. Nowadays the technology is available in game consoles and wearables. The technology has also been used in the healthcare sector for arthroscopic surgery and training surgical simulators as well as in the so called "exergames" which combines exercise and entertainments.


In Haptic feedback, the users adjust their movements regularly based on the feedback received from the system. This feedback can be provided both using voice and video from a human instructor. In order to have an optimal experience during a training session, the delay must be reduced sufficiently.


Using 5G communication, it is possible to have a very low latency application which can have a real-time interaction with users, ergo, a sense of 3D touch can be transmitted in real-time to the other party. This data can then be combined with some visualizations and edge-computing to provide different types of services which both industry and society can benefit from.


Please read: https://people.eecs.berkeley.edu/~yg/papers/hapvis.pdf


Thesis Project

  • You will work on Artificial Neural Network (ANN) and Machine Learning (ML) prototype in Python
  • Implement the results
  • Make visualization and documentation of the experiments, including proposals for possible needed extensions identified during the experiments


To be successful in the role you must have

  • Master degree in Computer Science, Applied Mathematics, Engineering Physics, Machine Learning or Artificial Intelligence
  • Software development experience in Python
  • Hands-on experience with one or more Machine Learning algorithms such as Regression, Clustering, Trees/Random Forest, Bayesian statistics, SVM, Neural networks, Deep learning or Reinforcement learning
  • 1+ years of experience working in applying Machine Learning
  • Experience with open source software, and frameworks such as Scikit-learn, Keras, Torch, TensorFlow, Caffe.
  • Knowledge in writing Hive or SQL queries for Data extraction
  • Data visualization skills and knowledge of frameworks and tools, e.g. Grafana, PowerBI, Tableau



Please compile your personal letter, CV and university transcripts in to one PDF document

Location: Sweden

Extent: 2 students for 30 HP each

Recruiter: Richard Tjong richard.tjong@ericsson.com

Master thesis supervisor at Ericsson: Lothar Wengerek, Manager for Enterprise Solutions & Systems

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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: https://www.ericsson.com/en/careers/job-opportunities/hiring-process


To read:




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Primary country and city: Sweden (SE) || || Stockholm || R&D

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