Research Fellow (Postdoctoral) - Two positions

Post status: Specific Purpose Contract – Full-time

Location:

Trinity College Dublin, The University of Dublin,
College Green, Dublin 2, Ireland

Reports to: Dr. Ivana Dusparic

Salary:

Commensurate with experience and achievement on the SFI Team Member Budget Scale (October 2024) Post Doctoral Researcher Level 2A/B (in the range €44,847-€55,740)

Hours of work: 39 hours per week

Closing date: 17:00 (BST) on Friday 20^th of December 2024. Late applications will be considered if the post remains unfilled.

Post Summary

We are seeking to recruit two post-doctoral research fellows to investigate novel reinforcement learning (RL) algorithms and their applications in IoT and edge cloud networks, within CONNECT - the Science Foundation Ireland Research Centre for Future Networks and Communications.

Position 1 (IoT networks): This project will investigate the use of multi-agent RL for sensor-scheduling in energy-constrained environments. Developed algorithms will need to be lightweight and are required to run on energy and resource-constrained devices. Algorithms will utilize Age of Information metric to learn appropriate update interval, taking advantage of observed correlation to reduce sensor system energy usage.

Position 2 (edge cloud networks): This project will investigate the use of multi-agent and multi-objective RL for optimisation of resource allocation in edge cloud networks.

The successful candidates are expected to make contributions to the state of the art in RL algorithms and their applications in communication networks.

The positions will be based in the CONNECT Research Centre at Trinity College Dublin under the direction of Dr. Ivana Dusparic, working in close collaboration with colleagues at other CONNECT partner Universities. In particular, position 1 will be involved close collaboration with Tyndall Institute, utilizing their renewable energy testbed.  

For informal inquiries please contact ivana.dusparic@tcd.ie.

Person Specification

• A PhD in Computer Science, Computer Engineering, Electronic Engineering, or a closely related field.
• An established track record of publication in leading journals/conferences on topics relevant to project.
• Demonstrates expertise in reinforcement learning and its applications in large-scale applications.
• Demonstrates excellent software engineering and programming skills.
• Demonstrates the ability to generate new ideas and link and build upon existing ideas to generate unique concepts and solutions with integrity.
• Demonstrates knowledge and understanding of the policy, practices and procedures that are relevant to the role including knowledge and understanding of research ethics, the broader University sector and external sponsor or funder policies.

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