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Master Internship AI Research RAN: Energy-efficient cell load balancing in 6G
Il y a 5 mois
Description
Why join Ericsson?
We are a world leader in the rapidly changing environment of communications technology – by providing hardware, software, and services to enable the full value of connectivity.
You’ll play a part in using your skills and creativity to push the boundaries of what’s possible. To build never-seen-before solutions to some of the world’s toughest problems.
Join a team of like-minded innovators driven to go beyond the status quo to build what’s next.
At Ericsson, you can be an explorer , a change maker and a force for good .
Our purpose: To create connections that make the unimaginable possible.
Our vision: A world where limitless connectivity improves lives, redefines business and pioneers a sustainable future.
Our values: Our culture is built on over a century of courageous decisions, in a place where co-creation and collaboration are embedded in the walls and where our core values of professionalism, respect, perseverance and integrity shine through in everything we do.
About this opportunity - Master Internship AI Research: Energy-efficient cell load balancing in 6G RAN using generative-AI decision making approaches.
The exponential increase of mobile traffic due to video and virtual reality applications results in high energy consumption. To make 5G and future 6G services sustainable, it is essential to reduce the telecom network carbon footprint. AI-driven management of radio RAN resources guided by intents, i.e. Service Level Agreement (SLA) between an operator and a service provider, can ensure the performance while minimizing the energy consumption. In this Master Internship, we will focus on a specific operation related to cell set selection and load balancing. The policy to associate users in cells and frequencies heavily impacts the resource allocation mechanism, the provided quality of service and the consumed energy. We aim to make these mechanisms AI-based for better and faster adaptability which will allow for better coordination of the available resources to satisfy the operator's aim described by the SLAs.
To tackle such decision-making challenges about user association and resource assignment we will use modern tools from Reinforcement Learning (RL). These permit us to learn the optimal policy from offline available datasets collected by measurements. Modern machine learning methods use generative AI models (e.g. transformers, diffusion models) for RL-based applications and demonstrate promising results in areas such as Atari and video games. We want to apply such modern decision-making tools to learn energy-efficient RAN management policies in future 6G telecom networks that can adapt to various SLA goals of the operators.
Join our Team
You’ll get the opportunity to
investigate different solution in the areas of AI-based networking, intent-based management and RAN applications, such as cell set selection. You will familiarize yourself with existing rule-based solutions to identify current shortcomings of the available approaches and where AI-based methods from the generative-AI literature can make a breakthrough. An important part of the research will be the study of the AI tools and the appropriate way to apply the right method to the problem at hand. To evaluate the quality of the solution the candidate will work on a proprietary simulator.
Key skills
To apply for this role, you are in your second year of Master or the final year of engineering school and be studying a degree in the following subjects (or related): Computer Science, electrical engineering, mathematics, or physics. To be successful in the role you have:
• good understanding of Machine Learning algorithms (Reinforcement Learning, Generative-AI, Neural Networks, times series, etc.).
• good foundation in practical programming skills, experience in Python and in using scientific Python packages such as PyTorch, Scikit-learn, Numpy, etc.
• ease with reading and implementing recent machine learning research articles from the established conferences (ICLR, ICML, NeurIPS etc).
• background in telecommunication networks will be appreciated, although not a must. Rather a genuine interest in the applications of the telecom (5G/6G) world and willingness to learn.
• excellent communication skills both in written and spoken English.
• knowledge about stack technologies and cloud architectures (optional but recommended): Git, Docker, Kubernetes.
Interns:
Interns who join us will enjoy an outstanding chance to make connections, to make change, to make a real difference. We are always looking for interns to become permanent members of our Ericsson team, so you’ll have the opportunity to discuss your future with us during your internship.
