Postdoctoral research fellow in Machine Learning applied to optical networks control plane

Novel optical access and metro networks are essential to support fast growing capacity
requirement, driven by future applications and services for 6G and beyond. Networks are also
evolving to support a large variety of signals across larger access and metro network areas. For
these novel scenarios, flexibility becomes an essential feature, driven by the development of
flexible components and open networks. These however require the development of intelligent
control planes to autonomously manage network requests, maintaining high availability and
optimal resource utilization.
One Post Doctoral researcher position is available for work in the area of intelligent AI-driven
control planes for optical communications networks. The work will involve the development
of AI models and intelligent control plane mechanisms to satisfy requirements of high
capacity, availability, heterogeneity, and low latency, required by future 6G networks.
The work will be developed around open optical systems and software defined networks
control planes and will include both access and metro networks.
The applicants should have a solid theoretical background on machine learning and optical
networks and willing to engage in testbed-oriented research. The work will be carried out in
the new OpenIreland research infrastructure, a large-scale testbed for experimentation in
optical, wireless and cloud technologies.
The position will be based in the CONNECT research centre at Trinity College Dublin, Ireland
and will be funded under the European Horizon project ECO-eNET and other national,
European, and industry projects. The researcher will have the opportunity to build their
research portfolio within a range of projects within CONNECT. The researcher will also be part
of the School of Computer Science and Statistics in TCD.
The position will be under the direction of Prof. Marco Ruffini and Prof. Dan Kilper