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Bell Labs - Ph.D. Position - Deep Reinforcement Learning for Radio Resource Management - ITN WINDMILL

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Applied R&D
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BLCTO Bell Labs & CTO
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19000003J0 Requisition #
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Nokia Bell Labs, France, is seeking to hire an Early Stage Researcher (ESR) to join the WindMill project. The project offers an excellent research and training programme:
 
•    Opportunity to join a network of leading Universities, research institutes and companies in the field of wireless communications and machine learning.
•    The ESR is primarily hosted by Nokia Bell Labs with stays in partner institutions (secondments).
•    Training programme including regular summer and winter schools to build technical skills as well as soft skills.
•    The salary is very competitive and composed by the following allowances: living, mobility and family (the latest only if eligible, see criteria of eligibility in the project’s website).

The ESR will be enrolled in the ED 160 EEA (Electricité, Electronique, Automatique) PhD programme at INSA Lyon.


Description:

Radio resource management (RRM) is a field of rich expert domain knowledge, often based on heuristic algorithms and manual finetuning of parameters. The goal of this project is to develop and apply state-of-the-art methods of deep reinforcement learning (RL) to RRM problems and to evaluate their performance with the help of large system simulations. Additionally, methods to reduce the implementation complexity and latency of RL algorithms will be investigated, both factors which currently limit their practical use. Finally, the problem of how to validate reinforcement learning algorithms for deployment in production with strict performance requirements will be studied.

  1. Identify relevant RRM problems that can be formulated as RL problems
  2. Develop and assess performance of state-of-the-art (deep) RL algorithms on the problems using large-scale system simulations
  3. Provide guidelines of how (deep) RL algorithms could be used in production

Expected outcomes are scientific publications in flagship conferences/journals and patent applications. The software implementation of deep RL algorithms and integration with our system simulator are important parts of the project. The students will receive training in deep RL and will be exposed to the practical challenges related to its industrial application.


About WindMill (https://windmill-itn.eu/):
With their evolution towards 5G and beyond, wireless communication networks are entering an era of massive connectivity, massive data, and extreme service demands. A promising approach to successfully handle such a magnitude of complexity and data volume is to develop new network management and optimization tools based on machine learning. This is a major shift in the way wireless networks are designed and operated, posing demands for a new type of expertise that requires the combination of engineering, mathematics and computer science disciplines. The ITN project WindMill addresses this need by providing Early Stage Researchers (ESRs) with an expertise integrating wireless communications and machine learning. The project will train 15 ESRs within a consortium of leading international research institutes and companies comprising experts in wireless communications and machine learning. This a very timely project, providing relevant inter-disciplinary training in an area where machine learning represents a meaningful extension of the current methodology used in wireless communication systems. Accordingly, the project will produce a new generation of experts, extremely competitive on the job market, considering the scale by which machine learning will impact the future and empower the individuals that are versed in it.

  1. An undergraduate degree and Master’s degree (or equivalent) in Electrical Engineering or Computer Science. Strong background in wireless communications and/or machine learning is an advantage.

  2. Excellent written and verbal communication, as well as presentation skills.

  3. Highly proficient English language skills.

  4. Excellent organisational skills, creative, innovative, independent thinker

  5. Motivation to collaborate in an interdisciplinary international team.

  6. Motivation to participate in training programs.

  7. Ability to travel and work in and outside Europe.

  8. Compliance with the ITN eligibility requirements.

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