Ali Bahadori-Jahromi

[Full tuition fees and a tax-free stipend of £18,000 per year.] Applications are invited for a funded PhD studentship at the University of West London focused on AI optimisation of green roofs and green facades for low-carbon, heat-resilient buildings . This project will develop an AI-enabled decision-support framework to evaluate how building-integrated green infrastructure can reduce operational carbon, lower building energy demand, and improve thermal comfort in urban settings. The research brings together building-performance modelling , machine learning , GIS , remote sensing , geospatial analysis , and multi-objective optimisation to identify the most effective green-infrastructure solutions for different building types, locations, vegetation conditions, and climate scenarios. The PhD will investigate: predicting energy, carbon, and thermal effects of green roofs and façades; identifying suitable configurations for selected building types; mapping where interventions could deliver the greatest benefits; evaluating performance under current and future climate conditions; and balancing energy, carbon, thermal, and practical considerations. The work will combine building simulations with machine-learning models so that performance can be predicted efficiently across a wider range of buildings and scenarios. GIS and satellite-derived data will support spatial assessment of suitable locations and environmental conditions. The project is primarily computational and does not require routine laboratory or fieldwork. The final scope will be refined with the successful candidate to ensure it is achievable within the PhD period. The expected start is September 2027 and the duration is 36 months . Funding: full tuition fees plus a tax-free stipend of £18,000 per year . The studentship is open to Home and International candidates . Eligibility highlights: applicants should have, or expect to obtain, a good first degree (First Class or Upper Second Class) and a master’s degree with Merit or Distinction in a relevant discipline such as building engineering, architecture, civil or environmental engineering, computer science, data science, or geography. Overseas applicants from non-English speaking countries must meet an IELTS 6.5 overall , with no component below 6.0 . Strong quantitative and analytical skills, Python experience, and background in AI/machine learning are required, alongside experience in one or more of GIS, remote sensing, building-energy/environmental modelling, optimisation, or statistical analysis. How to apply: submit the online application via the application link and include a research proposal outline prepared using the doctoral application template, a CV, and a transcript of your highest qualification. Overseas applicants should also provide proof of English proficiency. Informal enquiries may be directed to Professor Ali Bahadori-Jahromi at [email protected] .