AI-Driven Optimisation of Energy Efficiency and Circular Material Flows in Modern Construction Systems in the UK.

About the Project

The UK construction sector faces mounting pressure to decarbonise, improve resource efficiency, and meet net-zero targets by 2050. Buildings account for approximately 25% of UK greenhouse gas emissions, with embodied carbon from materials and operational energy use being key contributors (UKGBC, 2023). While circular economy principles—such as reuse, recycling, and material passports offer pathways to reduce environmental impact, their integration into mainstream construction remains limited due to fragmented data, inconsistent standards, and a lack of predictive tools (BEIS, 2021). Simultaneously, Artificial Intelligence (AI) has emerged as a transformative force in the built environment, enabling advanced modelling, optimisation, and decision-making across design and operational phases (Papapietro et al., 2025).

However, current applications often treat energy and material flows in isolation, failing to capture their interdependencies. There is a critical need for integrated frameworks that leverage AI to optimise both energy performance and circular material use across the building lifecycle, particularly within offsite and modular construction, which are gaining traction in the UK for their speed, quality, and sustainability benefits (Construction Leadership Council, 2022). This research addresses that gap by developing an AI-enhanced optimisation model tailored to UK construction systems, with a focus on retrofit and modular applications aligned with national decarbonisation strategies.

Aim

To develop and validate an AI-driven framework that simultaneously optimises energy efficiency and circular material flows in modern UK construction buildings, enhancing lifecycle sustainability and supporting net-zero transitions.

Academic qualifications

A first degree (at least a 2.2) ideally in Surveying (All pathways), Environmental Science, Architectural Technology or Civil Engineering.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted.

Essential attributes:

• Good fundamental knowledge of Surveying (All pathways), Environmental Science, Architectural Technology and Civil Engineering.
• Understanding of AI and Machine learning
• Understanding of sustainable construction

Desirable attributes:

• Understanding of Energy Efficiency

APPLICATION CHECKLIST

• Completed application form
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (download)
• Research project outline of 2 pages (list of references excluded). The outline may provide details about:
  1. Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
  2. Research questions or objectives.
  3. Methodology: types of data to be used, approach to data collection, and data analysis methods.
  4. List of references.
• Statement no longer than 1 page describing your motivations and fit with the project.
• Evidence of proficiency in English (if appropriate)

To be considered, the application must use the advertised title as project title

For informal enquiries about this PhD project, please contact Dr Nimi Dan-Jumbo - N.Dan-Jumbo@napier.ac.uk