Job Description

Recently, self-driving networks have been receiving much attention which could achieve resource efficiency, provide improved quality of service, and handle critical events such as congestion, failures, and attacks effectively. Self-driven networks can dynamically respond to events (such as congestion, failure, attack etc.), and implement the strategy to manage the network – with minimal human interaction at any stage. In this project, we aim at developing AI/machine learning/deep learning based techniques for network control and services providing resilience in networks. The scope of the work for the Research Fellow position requires development of techniques and algorithms, analysis, and performance study.

Qualifications

Interested candidates who are passionate for research with strong academic and research record and Ph.D.  degree in Computer Engineering/Computer Science/Electrical, Electronics, Telecommunication Engineering and other related disciplines are eligible for this position. The Research Fellow should have knowledge/interest/experience in one or more of the following areas.

•    Doctorate degree in related field
•    Artificial intelligence/machine learning/deep learning
•    Optimization techniques
•    Computer networks
•    Network softwarization, virtualization – NFV, SDN
•    Open to fixed term contract.