PhD Studentship: Resilience-based Management of Transport Infrastructure Enhanced by Digital Data and Artificial Intelligence (AI)

We aim to develop a new data-driven tool to unravel context-dependency and enhance resilience-based management of transport infrastructure assets, by integrating computational modelling and AI. The primary objective of this PhD program is to enhance advanced Finite Element (FE) models by incorporating data sourced from diverse outlets like digital twins, point clouds, and/or other forensic evidence, which may be acquired through inspections. The aim is to augment the predictive capabilities of models concerning transport assets and/or networks, including bridges, roads, and/or railways. The overarching goal is to support decision-making rooted in resilience considerations. These refined models will allow for the prediction of asset conditions and the probability of failure under various hazard scenarios, such as climate-related events or human-induced stressors, like explosions resulting from acts of terrorism or similar hostility attacks. The research endeavours to develop a toolkit for classifying assets based on their performance, ultimately aiding decision-makers in addressing accelerated asset deterioration due to climate change and High-Intensity Low Probability events.

Candidate essential and desired skill set:

• Basic knowledge on digital data and digital twins
• Numerical modelling
• Statistical methods
• Willingness to learn computational modelling and Artificial Intelligence
• Knowledge of digital data and the significance of digital twins

Deadline for applications (see steps 1-4 below need to be completed by): 25 February 2024

Roadmap of your application:

1. Send a 2-page CV to S.A.Mitoulis@Bham.ac.uk stating if you are a home or international student and if you are looking for a scholarship or you are self-funded. In your CV, please add a link to your LinkedIn, Google Scholar and/or Scopus account. The supervisor writes back to you within 3 days.
2. Apply on SITS portal https://sits.bham.ac.uk/lpages/EPS015.htm
3.  Supervisor assesses your application.
4. An interview is arranged if your case is strong*
5. If you are selected after the interview, the supervisor requests an offer letter to be sent to you.
6. With the offer letter you can then apply for the EPSRC DT Scholarship scheme OR Self fund your studies.
7. If you are applying for the EPSRC DT Scholarship you will have to work on the application with your supervisor to submit your application by the 15th of March 2024, 17:00.
8. If you are self-funded, you can start your PhD whenever is convenient.
9. Full time commitment is expected from candidates that will be applying for the EPSRC DT Scholarship scheme. Part time will only be considered for self-funded PhD students.

*If you are international student you will have to obtain an ATAS immediately after step 4 and if the supervisor gave you positive feedback

Funding notes:

• Applicants may obtain funding from the School of Engineering or have their own funding to cover the fees and living expenses.
• EPSRC Doctoral Training Programme PhD studentships cover the home tuition fee and stipend.
• A salary top-up is possible for competitive candidates.

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