PhD Decarbonised and Resilient Energy Districts through Data-Driven Building Retrofitting and Smart Grid Solutions

Project Description

Cities face an urgent dual challenge: rapidly decarbonising their building stock while maintaining electricity grid resilience as heating and transport become increasingly electrified. Although retrofit programmes are accelerating, most existing approaches treat building retrofits and electricity networks separately, overlooking key interactions between demand growth, flexibility, embodied and operational carbon, and local grid constraints.

This PhD project addresses this gap by developing an integrated, data-driven framework for neighbourhood-scale retrofit and smart grid planning in Scotland. Building on an ERPE Seed-funded Edinburgh case study, the research will extend the analysis across diverse Scottish urban contexts.

The project will combine building physics-based modelling, AI-driven optimisation, life-cycle carbon assessment, and smart grid simulation to evaluate large-scale retrofit packages, electrification pathways, and distributed energy storage options. The work will be informed and validated through stakeholder co-design workshops involving electricity network operators, local authorities, housing providers, and community energy groups.

The research aims to deliver both high-quality academic outputs and practical decision-support tools to inform retrofit policy, grid planning, and equitable net-zero transitions.

Research Themes and Methods

The PhD will involve:

• Developing baseline urban building stock models using EPC and SERL datasets
• Modelling retrofit and electrification scenarios at neighbourhood scale
• Assessing embodied–operational carbon trade-offs using LCA methods
• Simulating grid impacts using aggregated network data
• Applying AI-based optimisation to explore cost-effective and resilient pathways
• Engaging with stakeholders through structured workshops

The student will be embedded within a cross-institutional research collaboration between Heriot-Watt University and the University of Edinburgh, supported by weekly meetings and joint supervision. The project is part of the Data-Driven Retrofit and Smart Grid Collective, providing access to shared datasets, modelling platforms, and industry partners. This environment offers strong interdisciplinary training and real-world impact.

Selection Process

There is a two-step selection process:

1. Applications will be reviewed by the supervisory team. Shortlisted candidates will be invited to attend a technical interview with the project supervisors (January 2026)
2. The selected candidate will be put forward for a final competitive interview with the Edinburgh Research Partnership in Engineering (ERPE) panel (February 2026)

How to Apply (Stage 1 – Informal Application)

At this stage, interested candidates should apply directly to the supervisors, not through a formal PhD application.

Please email the following to Dr Sahar Mirzaie (s.mirzaie@hw.ac.uk) and Dr Desen Kirli (desen.kirli@ed.ac.uk):

• CV (max. 2 pages)
• Cover letter outlining your background, research interests, and motivation for the project (max. 2 pages)

Application deadline: Tuesday 16:00BST 20 January 2026, 4pm

Informal enquiries are welcome.

Equality, Diversity and Inclusion

We warmly encourage applications from candidates from groups underrepresented in engineering, energy, and data-driven research. Selection will be based on merit, research potential, and alignment with the project.