PhD Studentship: Artificial intelligence to develop tailored construction materials for road infrastructure
- Closing Date
- Friday, 31st May 2019
The main aim of this project is to use artificial intelligence algorithms for optimization of the composition of materials for road infrastructure, to maximize their durability and resistance to traffic loads and environmental conditions.
Description (for advertisement)
We aim to revolutionize the design of construction materials for road infrastructure. Most of the used materials to build roads are asphalt or concrete; the problem is that their design is still made by the trial-and-error method, which is a lengthy process and is prone to human errors. To fully automatize the design of road materials with extreme durability under realistic service life conditions, the successful candidate will combine advanced machine learning techniques and Multiphysics computational tools in a virtual reality environment.
Innovative aspects of this thesis will be (i) the computational inpainting of virtual asphalt or concrete; (ii) the application of an innovative discrete Multiphysics modelling method; (iii) the use of optimization and unsupervised machine learning algorithms to define the asphalt or concrete composition that maximize the durability of road surfaces.
The outcome of the project will be a computational tool that can be used by the construction industry to design asphalt or concrete with extreme durability and the lowest cost, under given service conditions. In order to ensure the applicability of the software for the industrial sector, the candidate will interact with several construction companies and industrial laboratories during the project.
The intended start date is 1st of April 2019 (earlier start dates will be considered). The studentship covers both tuition fees and a tax-free student stipend at RCUK rates for 2019/20 academic year. Duration is 3 years.
Due to funding restrictions, this studentship is open to UK/EU candidates only.
We are seeking an enthusiastic and highly motivated person with good interpersonal skills and a keen interest in research. You must have at least a 2:1 honors degree or a distinction or high merit at MSc level (or international equivalent) in physics, materials science, mathematics or engineering.
To apply for this position, send the CV directly to Dr Bahman Ghiassi (firstname.lastname@example.org) or Dr Alvaro Garcia (email@example.com). Informal enquiries about the vacancy can also be asked to the same contact persons.