PhD Studentship: Reducing tunnel volume loss using data processing techniques

Applications are invited for a PhD studentship in the Department of Engineering. The successful candidate will have the opportunity to work on an investigation into tunnelling-induced ground movements and their effects on nearby structures.

Summary of the thesis project

The project will be, firstly, collating two Big Data sets captured during tunnelling works (settlement and TBM driving data) and conducting a series of interrogations to establish the most important variables. The next stage is to employ data processing techniques to create the relationships necessary to predict settlements for a given TBM data set. The aim for this section of the proposed work will be to predict settlement data further along a route using TBM data from earlier in the drive.

The validation of the modelling will be extended by a series of experiments with carefully controlled conditions which will in turn supply more data for the AI model. The data will be made available if requested for alternative analyses to be conducted by HS2 or its nominated suppliers. The model and all of the HS2 tunnelling data will be not only shared with HS2 and its nominated suppliers, but it will also be wholly non-proprietary and published as part of the academic record and learning legacy of this project.

Eligibility and requirements 

The candidate should have a first or upper second-class BEng/MEng (or equivalent, or higher) degree in Civil Engineering or Computational Physics. They should demonstrate aptitude for original research.

The candidate should possess a good understanding of construction processes and data processing techniques (i.e. coding). A candidate who demonstrates exceptional aptitude in one or more of these areas (as evidenced, for instance, through strong academic credentials or research papers in reputable, peer-reviewed journals/conferences) may be accorded preference. Ideally, the successful candidate should have proven skills in laboratory testing and data analysis techniques. 

A doctoral candidate is expected to meet the following pre-requisites for their PhD: 

• Demonstrate a sound knowledge of their research area
• Achieve and demonstrate significant depth in at least a few chosen sub-areas relevant to their primary research area
• Demonstrate the ability to conduct independent research, including a critical assessment of their own and others’ research

What we offer

The scholarship is for 3 years and will provide an annual tax-free stipend of £21,000 and tuition fees (‘Home’). An extra £1,500/year salary supplement will be offered to all successful candidates from underrepresented communities. In particular, the stipend supplement will be reserved for female, LGBTQ+ and disabled applicants.

Each student may also have the opportunity to earn around £2,200/year on an average (max. is around £4,300/year) through a teaching assistantship.

How to apply

Applicants are welcome to apply directly in link below.  For queries regarding the application process, email pgr.sst.enquire@city.ac.uk.  For queries regarding the project, please contact Dr Sam Divall sam.divall@city.ac.uk

To apply online, please click the 'Apply' button, above.

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