location: South Kensington, London (mixed working possible by agreement)

About the role:

You will join the EPSRC-funded project “Behavioral Data-Driven Coalition Control for Buildings”, a pioneer in distributed, data-driven control approaches that enable building groups to form alliances to deliver reliable, low-carbon energy services. In close collaboration with UK Power Networks, SSE Energy Solutions and the University of East London, it will develop powerful economic model predictive control (MPC) algorithms, innovative alliance formation techniques, and validate them through high-resolution simulations.

what would you do:

You will design, implement and validate innovative data-driven economic model predictive control (MPC) methods to enable large groups of buildings to dynamically form alliances and provide resilient energy services. Your work will incorporate advanced robust MPC technologies, including scenario-based and pipelined approaches, to ensure reliable operation despite significant uncertainty in weather, demand and energy prices.

In collaboration with UK Power Networks and SSE Energy Solutions, you will apply your methods in detailed simulation studies using Imperial’s HPC facilities, evaluating performance in real-world scenarios. You will regularly present your results to academic and industrial audiences, publish in leading journals, and actively contribute to the development and deployment of open source software. In addition, you will support junior researchers and graduate students on your team.

Working closely with collaborators at the University of East London, you will combine powerful MPC algorithms with advanced coalitional control strategies, identifying optimal ways for building groups to share resources and benefits. You will investigate and measure the trade-offs between individual goals and collective outcomes, with an emphasis on scalability, economic viability and robustness in the face of realistic operational uncertainty.

What we are looking for:

• PhD (or equivalent) in Control Engineering or a closely related discipline.
• Proven track record in at least two areas: model predictive control, robust/distributed control, data-driven selection/control, and numerical optimization.
• Strong programming skills in at least two of the following: Julia, MATLAB, C/C++, and Python.
• Demonstrate the ability to produce high-quality journal publications and scientific manuscripts.
• Experience presenting research clearly at international conferences and industry workshops.
• Proven ability to effectively manage your time and prioritize tasks to meet research deadlines.
• Experience working collaboratively within multi-disciplinary teams or industry partnerships.
• Enthusiasm to mentor junior researchers and contribute positively to a collaborative research environment.
• Desirable: Experience building energy applications, energy systems, cooperative or coalitional game theory, or high-performance computing workflows.

What we can offer you:

• You will join a vibrant research community based on our central London campus in South Kensington, offering easy access to cultural institutions, excellent transport links and a stimulating research environment.
• An opportunity to shape next generation control theory within a world-leading research group
• You can find more details about the benefits we offer by reading the full job advert www.Imperial.ac.uk/jobs

Post available from 1^street March 2026 for up to 24 months, based in the Department of Electrical and Electronic Engineering at Imperial College London (South Kensington).

To apply, please click the “Apply” button above.

Please be sure to include the completed application form with your order.

Closing date: Midnight on Sunday 2^{Second abbreviation} November 2025