PhD Studentship in AI and Network Science for Modern Power Systems Analysis Imperial College London in United Kingdom

Imperial College London invites applications for a fully funded PhD studentship in the Control and Power Group, Department of Electrical and Electronic Engineering. This position offers an exciting opportunity to work at the intersection of network science and artificial intelligence, focusing on the analysis and optimization of modern power systems in the era of renewable energy.

The project is supervised by Dr. Homayoun Hamedmoghadam (ICRF Fellow) and Professor Tim Green (Professor of Electrical Power Engineering), both at Imperial College London. The research aims to address the challenges posed by the transition to renewable energy sources such as wind, solar, and batteries, which are integrated into power grids via electronic inverters. This shift fundamentally changes the operation and stability of power networks, requiring new theoretical and practical approaches.

The central vision of the project is to combine the strengths of Network Science and Artificial Intelligence to develop innovative methodologies for the design, expansion, and control of power systems. The student will identify minimal yet high-impact interventions—such as structural modifications, control placements, and operational adjustments—to optimize grid architecture and ensure reliable operation in a net-zero future. The research will focus on maximizing the security and resilience of power networks while minimizing infrastructure costs, delivering significant societal and economic benefits.

Key objectives include:

• Conducting a comprehensive literature review on network science analytics of power system stability, net-zero transition impacts, and structural interventions for controlling network dynamics.
• Analyzing the dynamical effects of renewables integration, including desynchronization phenomena, instability mechanisms, and cascading failure events.
• Developing theoretical frameworks and practical tools for network upgrade and restructuring to reinforce resilience.
• Designing AI pipelines that ground the learning of power system dynamics in physical reality and network science interpretation.

The successful candidate will be based at Imperial College London, working within a world-leading research environment. The studentship is funded by the Department of Electrical and Electronic Engineering and covers home-level tuition fees, a tax-free stipend at the UKRI London rate (£22,780 per year for 2025/26) for 3.5 years, and support for research expenses and travel to collaborators and conferences. Overseas applicants are welcome but must cover the difference between Home and Overseas tuition fee rates.

Eligibility: Applicants should hold a first-class Master’s degree (or equivalent) in Computer Science, Electrical/Electronic Engineering, Mathematics, Physics, or related fields. Suitable backgrounds include machine learning, network science, control engineering, and power engineering. Candidates must be highly motivated and meet Imperial College London’s postgraduate eligibility requirements.

Application Process: Apply online via the provided link, including a cover letter and CV. For project-specific enquiries, contact Dr. Homayoun Hamedmoghadam at [email protected]. For application process queries, email [email protected]. Early application is recommended as the position may be filled before the official closing date of 31 July 2026.

Imperial College London is renowned for its focus on science, engineering, medicine, and business, consistently ranked among the top universities globally. The Department of Electrical and Electronic Engineering offers a vibrant research community and excellent facilities for interdisciplinary work.