Publisher
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M Sajjadian

4 months ago

Multi‑Scale Simulations and Generative Design for Net Zero Built Environment Edinburgh Napier University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD Project (Students Worldwide)

Deadline

Expired

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Country

United Kingdom

University

Edinburgh Napier University

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Where to contact

Official Email

Keywords

Computer Science
Environmental Science
Urban Planning
Civil Engineering
Architecture
Built Environment
Energy Efficiency
Building Physics
Thermal Comfort
Multiscale Modeling
Urbanism
Generative Modeling
Computational Modelling
Carbon Emissions
Urban Geography

About this position

This PhD project at Edinburgh Napier University focuses on advancing the design of net zero built environments through the integration of multi-scale simulations and generative design. The built environment is a major contributor to global carbon emissions, accounting for approximately 40% worldwide, making it a critical area for intervention in the pursuit of net zero targets. While progress has been made in sustainable materials and renewable energy, the architectural and urban design strategies themselves remain pivotal in determining environmental performance. Traditional design approaches often rely on intuition and incremental changes, limiting the ability to fully leverage the complex interactions between materials, building envelopes, HVAC systems, and urban morphology.

This project aims to address these limitations by employing computational models that operate across multiple scales—from individual building components and façades to entire buildings and urban neighborhoods—coupled with AI-driven generative design algorithms. This approach enables the systematic exploration of a wide range of design configurations, each evaluated against multiple performance criteria such as operational and embodied energy, carbon emissions, thermal comfort, and spatial functionality under realistic scenarios. The research is particularly significant given the rapid urbanization, increasing climate mandates, and evolving architectural practices. It seeks to provide designers, policymakers, and industry practitioners with robust tools for creating architecturally coherent, energy-efficient, and socially equitable urban environments.

By bridging architectural design with computational modeling and artificial intelligence, the project contributes to evidence-based design and supports the development of resilient, contextually responsive, and low to zero carbon built environments. The intellectual and practical contributions of this research position the investigator at the intersection of architecture, computational science, and environmental engineering, fostering the development of methodologies that actively shape architectural form. The project is fully funded for UK and international students, covering tuition fees and providing a standard living allowance.

Applicants should have a first-class honours degree or distinction at master level in Architecture or a closely related field, with strong knowledge in building physics, computational modelling, and AI-driven design. The application deadline is January 9, 2026. For informal enquiries, contact Dr M Sajjadian at [email protected].

Funding details

Funded PhD Project (Students Worldwide)

What's required

Applicants must have, or expect to achieve by the start of the studentship, a first-class honours degree or a distinction at master level, ideally in Architecture or an equivalent subject. A strong foundation in architecture, understanding of building physics, competence in computational modelling and simulation, and some knowledge of AI and generative design methods are essential. Only candidates with a first-class honours degree or distinction at master level in a relevant subject will be considered, or those with equivalent achievements. Practical experience in research or industry is desirable. English language proficiency is required, with an IELTS score of at least 6.5 (no component below 6.0) or equivalent qualifications.

How to apply

Complete the application form and quote the reference 'SCEBE1125' on your form. Submit a CV, two academic references using the Postgraduate Educational Reference Form, a two-page research project outline, a one-page motivation statement, and evidence of English proficiency if appropriate. Use the advertised title as the project title.

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