CIFRE thesis (PhD) : Resilience-as-a-Service for xRAN slices using Machine Learning methods
Ideal candidate should a solid mathematical background, especially in probability and statistics. The candidate should be eager to tackle new challenges in the area of machine learning and deep learning, distributed optimizations. He/she should have a good background in networking technology and familiar with LTE RAN and 5G. It is imperative that the candidate has a perfect proficiency in Python/C/C++ or tensorflow/keras, or other scripting languages. Lastly, the candidate should demonstrate a good motivation and autonomy. Good communication skills (written and verbal) in both English and French are required.