Funding

Self-funded

Project code

SCS10730529

Department

School of Civil Engineering and Surveying

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project. 

The PhD will be based in the School of Civil Engineering and Surveying and will be supervised by Dr Quan Phung, Dr Salem Chakhar and Dr Sepehr Abrishami.

This project is positioned at the intersection of artificial intelligence, Design for X (DfX), and construction project management. It responds to a persistent challenge in construction: early design and planning decisions often determine the feasibility, efficiency, and long-term value of a project, yet these decisions are commonly made with incomplete information and limited integration across disciplines. DfX provides a useful lens for addressing this issue by encouraging project teams to consider requirements such as constructability, safety, sustainability, logistics, maintainability, and lifecycle value from the outset. The project therefore investigates how AI can strengthen early-stage decision-making by enabling project teams to assess design choices more systematically and anticipate their implications before construction begins.

 

 

The work on this project will: 

  • Focus on DfX as a project-level decision-support mechanism rather than a narrow design checklist
  • Examine how AI can capture and organise knowledge from previous projects, expert judgement, planning documents, risk information, and design reviews to support more informed option appraisal.
  • Explore how competing project priorities can be evaluated together, rather than in isolation, allowing trade-offs between cost, time, safety, buildability, carbon, and operational requirements to be made more explicit. 
  • May include a DfX criteria structure, an AI-supported evaluation process, and practical guidance for embedding DfX thinking into design management and project governance. 

 

This project investigates how artificial intelligence can support Design for X (DfX) decision-making during early-stage construction project planning. Many delivery problems, including rework, sequencing difficulties, safety risks, cost escalation, inefficient logistics, and weak sustainability performance, are often linked to decisions made during design and planning. However, these early decisions are commonly assessed through fragmented reviews, discipline-specific expertise, and informal lessons learned, making it difficult for project teams to evaluate the wider consequences of design alternatives in a systematic way. The project aims to develop an AI-enabled DfX decision-support framework that helps project teams assess early design options against multiple project performance requirements. 

 

The research will examine how DfX principles, such as design for constructability, safety, sustainability, logistics, and maintainability, can be translated into structured decision criteria for construction project planning. AI methods may then be used to organise project knowledge, identify risks, compare design alternatives, and make trade-offs between competing objectives more explicit. 

 

The research is expected to combine literature review, expert consultation, framework development, and empirical validation through case studies or scenario-based evaluation. Its main contribution is to reposition DfX as a project-management decision-support approach rather than only a technical design principle. By integrating AI, DfX, and early-stage planning, the project aims to help clients, project managers, design managers, and contractors make more informed decisions before construction begins, thereby improving downstream project performance and supporting safer, more efficient, and more sustainable construction delivery.

 

 

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only – eligibility criteria apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. 

English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

International students will require a study visa from UKVI to pursue the degree in the UK. If the research is in a sensitive or technological subject, the student may also need to secure an Academic Technology Approval Scheme (ATAS) certificate from the UK Foreign Office.

 

 

How to apply

We’d encourage you to contact Dr Quan Phung ([email protected]) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Civil Engineering PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code SCS10730529.