Funding

Self-funded

Project code

SCS10760529

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 Abba Mahmud, Dr Quan Phung and Dr Salem Chakhar.

The increasing use of AI-enabled systems in construction safety management is changing how project risks are identified, monitored, communicated, and controlled. Tools such as predictive safety analytics, computer vision, digital twins, wearables, drones, and AI-assisted reporting can support safer project delivery, but they also introduce new governance challenges around responsibility, competence, data use, human oversight, and accountability. While CDM 2015 regulations provides the core regulatory framework for managing health and safety duties in construction projects, it does not provide detailed guidance on how duty holders should manage AI-enabled safety systems. This research therefore addresses the need for a governance-focused maturity model that helps construction organisations assess and improve their capability to use AI safely, responsibly, and in alignment with CDM 2015 principles.

 

 

 

 

The work on this project will: 

  • Shift the discussion from technical AI development to project governance, safety management, and regulatory implementation. 
  • Contribute to the development of a maturity model that evaluates how prepared construction organisations are to govern AI-enabled safety systems across key areas such as duty holder responsibility, procurement, competence, risk assessment, worker consultation, data governance, human decision-making, and continuous improvement. 
  • Research to produce a practical guidance Framework to clients, principal designers, principal contractors, designers, contractors, and safety managers with a structured way to understand and manage AI-related safety risks within existing project-management processes.

 

This research aims to develop and validate a governance maturity model for AI-enabled construction safety management, with the final output positioned as a supplementary guidance framework to CDM 2015 regulation. 

The study will examine how construction organisations can govern AI-enabled safety systems across the project lifecycle, particularly in relation to duty holder accountability, competence requirements, procurement decisions, risk assessment, data governance, worker consultation, human oversight, and continuous improvement. 

Methodologically, the study combines critical literature review, semi-structured interview, questionnaire survey for data collection and further analysis techniques of system dynamics, structure equation modelling/fuzzy DEMATEL. The proposed maturity model will define progressive levels of governance capability, ranging from ad hoc AI adoption to integrated and continuously improving AI-enabled safety management. These maturity levels will then inform the development of supplementary CDM-oriented guidance, including a duty holder responsibility matrix, AI safety risk checklist, competence guidance, procurement considerations, and recommendations for integrating AI-related information into pre-construction planning, Construction Phase Plans, site monitoring, incident learning, and post-project review. 

 

 

 

 

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 Abba Mahmud ([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 SCS10760529.