A PhD Studentship in AI and Network Science for Modern Power Systems Analysis

About the Project

Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Group, Department of Electrical and Electronic Engineering). The position offers a unique opportunity to explore the cutting-edge intersection of network science and artificial intelligence, with the broad goal to investigate and optimise power infrastructure.

The project will be supervised by Dr. Homayoun Hamedmoghadam (ICRF Fellow, Imperial College London) and Prof. Tim Green (Professor of Electrical Power Engineering, Imperial College London).

Summary of Project:

Power grids are undergoing a major transformation with the full conversion to renewable energy sources such as wind, solar, and batteries. These resources interface with the grid through electronic inverters, fundamentally altering their grid role to the conventional power plants. Therefore, the contemporary foundations that have long underpinned the operation of power grids, may no longer be valid with high penetration of renewable resources—despite the ever-increasing societal and economic importance of power systems. The research in this project pertains to the design, expansion, and control of the modern power systems with the aim of ensuring the reliable operation in the net-zero era. The central vision is to empower the theory-rich Network Science framework with Artificial Intelligence to bring fresh insights into the architecture of renewable-integrated power systems.

A key objective is to identify minimal yet high-impact network interventions, such as targeted structural modifications, control placements, or operational adjustments, enabling a principled rethinking of how power networks should be designed and/or upgraded. From a network science perspective, the ability to pinpoint interventions with maximal benefit is highly sought after and can reveal new principles of emergent functionality in complex interconnected systems. The research seeks solutions that consequently minimise the cost of infrastructure improvements while maximising the security of operation, delivering tangible societal and economic benefits.

Within this project, the PhD student will develop synergistic methodologies combining network and power systems theory with AI, with the goal of optimizing existing grids and devising robust strategies for system upgrade and expansion under increasing renewables penetration. The PhD student will be expected to:

1. Undertake a literature review on network science analytics of power system stability, the impact of the net-zero transition, structural interventions for controlling network dynamics, and so on.
2. Analyse the dynamical effects of renewables integration, with emphasis on desynchronization phenomena, instability mechanisms, and cascading failure events.
3. Develop theory and tools to address fundamental questions pertaining to network upgrade and restructuring for resilience reinforcement.
4. Tailor AI pipelines, grounding the learning of power system dynamics in physical reality and network science interpretation of system properties, to address the identified challenges.

Funding

The PhD studentship is funded by the Department of Electrical and Electronic Engineering (EEE) and includes home-level tuition fees, a stipend for three and a half years at the UKRI London rate (approximately £22,780 per year (tax-free) for 2025/26), and support for research expenses and travel to collaborators and conferences. The post is open to home and overseas applicants, but only home fees will be covered by this scholarship. Overseas applicants will be expected to cover the difference between the Home and Overseas tuition fee rate.

Duties and responsibilities

The responsibilities include studying the relevant literature, defining the research problems based on the project descriptions, conducting independent research, regularly reporting progress and results in both oral and written format, collaborating with other team-members, and writing reports/papers of the research outcomes when appropriate. The successful candidate will be based at the Control and Power Group in the Department of Electrical and Electronic Engineering at Imperial College London.

Essential Requirements:

Applicants should have a first-class Master’s degree (or equivalent) in Computer Science, Electrical/Electronic Engineering, Mathematics, Physics, or related areas. Suitable backgrounds for these PhD positions include, but are not limited to, machine learning, network science, control engineering, and power engineering. Applicants should be highly motivated individuals with a keen interest in conducting interdisciplinary research. Students must also meet the eligibility requirements for Post-Graduate Studies at Imperial College London.

Further Information and application

For enquiries, please contact Dr. Homayoun Hamedmoghadam (h.hamed@imperial.ac.uk).

Please click HERE to apply. The application should also include a cover letter, and your CV.

Full guidance on application process is available HERE. Any further queries regarding the application process should be directed to eee.pgadmissions@imperial.ac.uk.

Closing Date: 31 July 2026 (Note however that early application is highly recommended as position will be filled as soon as a suitable candidate is found, which might be before closing date.)