Multi‑Scale Simulations and Generative Design for Net Zero Built Environment

About the Project

The built environment is responsible for approximately 40% of global carbon emissions [1], making it a critical frontier in the global pursuit of net zero targets. While advances in sustainable materials and renewable energy technologies are contributing to emission reductions, the fundamental architectural and urban design strategies employed remain among the most influential determinants of environmental performance. Traditional design workflows often rely on intuition, precedent, or incremental modifications, which constrain the ability to fully exploit the interactions between material properties, building envelope performance, HVAC systems, and urban morphology. These limitations restrict accuracy and the potential to reach zero carbon architectural solutions.

This research aims to overcome these challenges through the integration of multi-scale simulations and generative design in the architectural design process. By employing computational models that operate across multiple scales; from individual building components, assemblies, and façades to complete buildings and urban neighborhoods coupled with AI-driven generative design algorithms, the project enables the systematic exploration of high number of design configurations for maximum effectiveness and efficiency. Each configuration can be evaluated against multiple performance criteria, including operational and embodied energy, carbon emissions, thermal comfort, and spatial functionality, under realistic environmental and operational scenarios. This multi-objective approach ensures that architectural decisions are informed quantitatively between the variables.

The significance of this research is highlighted by the convergence of rapid urbanisation, climate imperatives, and evolving architectural practice. As cities expand and carbon reduction mandates become more stringent, designers, policymakers, and industry practitioners require tools capable of producing architecturally coherent, energy-efficient, and socially equitable urban environments. By bridging architectural design with computational modeling and AI, this project addresses key debates in evidence-based design, offering a framework that supports resilient, contextually responsive, and low to zero carbon built environments.

This research provides both intellectual and practical contributions. It situates the investigator at the intersection of architecture, computational science, and environmental engineering, enabling the development of design methodologies that actively shape rather than merely evaluate architectural form. By advancing multi-scale, AI-informed generative design strategies, the project aims to produce actionable insights for the creation of net zero architecture and urban landscapes, directly contributing to one of the most urgent global challenges of our era.

[1] Carlin D. 40% of emissions come from real estate; here's how the sector can decarbonize. United Nations Environment Programme Finance Initiative. 2022 Apr 13.

Academic qualifications

Have, or expect to achieve by the time of start of the studentship a first-class honours degree, or a distinction at master level, ideally in Architecture or equivalent with a good fundamental knowledge of Architecture, Building Physics, Computational Modelling and Simulation, Artificial Intelligence and Generative Design.

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. Full details of the University’s policy are available online.

Essential attributes:

• Strong foundation in architecture
• Understanding of building physics
• Competence in computational modelling and simulation
• Some knowledge of AI and generative design methods
• Only a first-class honours degree, or a distinction at master level in a subject relevant to the PhD project will be considered, or equivalent achievements.

Desirable attributes:

• Practical experience in research or industry will be considered an advantage.

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.
• The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.
• 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