Development of machine-learning based high performance composites for constructions

   Department of Civil Engineering

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  Dr Bahman Ghiassi  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Composite materials (cement-based or polymeric-based) have been widely used for several decades for the construction or repair of the infrastructure or built environment. However, the design of these materials has been mainly based on trial-and-error methods, which are lengthy, prone to human errors and lack generality to be applied to new composites. In this project, PhD applications are invited to develop artificial intelligence models coupled with physics-based laws to establish composition-property links in these composites so that maximum performance is achieved with minimum materials usage. The project could be focused on cement-based or polymeric-based composites depending on the interest of the candidate. Experimental testing and computational modelling will be used for the validation of the developed models and for the evaluation of the performance of the optimised composites. During the course of the multidisciplinary project, you will receive extensive hands-on training on advanced materials modelling and testing technologies, you will closely work with world-renowned academics and experts in the field, and you will have the opportunity to interact with industrial partners.

Engineering (12)

Funding Notes

We are seeking an enthusiastic and highly motivated student with good interpersonal skills and a keen interest in research. You must have, or expect to achieve, at least a 2:1 honors degree or a distinction or high merit at MSc level (or international equivalent) in Civil Engineering, mathematics or a related subject. Preference will be given to candidates with educational and/or research experience in engineering.

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