PhD Studentship: Machine Learning in Tunnel Boring Excavation

Funding for (UK/EU/o’seas): UK/EU (UK settled status) with permanent UK residency

Funding amount: Minimum £17,668 subject to eligibility status and confirmation of award

Hours: Full time

Contract: temporary

Closing date: 31 January 2023

Project Title: Machine Learning in Tunnel Boring Excavation

The project:
J. Murphy and Sons have been investigating using machine learning in tunnelling by applying supervised learning techniques to predict construction duration and are interested in exploring new and continued applications of machine learning in tunnel boring. The primary aim of the project is to develop a process to enable the full use of machine learning in Tunnel Boring such that it can become an effective decision tool at all stages of the project from bidding and planning to execution.

The project would entail the following stages:

1. Literature Review including increasing competencies in Machine learning and Geotechnical Engineering as required.
2. Collect and analyse data from real case studies and ongoing projects.
3. Develop machine learning algorithms to predict speed of tunnelling, incorporating all the necessary variables and the expected uncertainties in ground conditions.
4. Test the developed algorithms for a range of different scenarios and independent case studies to demonstrate their reliability while determining the boundaries of applicability.

The project will be co-supervised by academics in Geotechnical engineering and Data Science/Machine Learning as well as being supported by civil, mechanical and geotechnical experts from J Murphy and Sons.

How to apply:

Prior to application, please contact Dr Dimitris Karamtros, Dr Andrea Diambra or Dr James Pope.

To apply for this studentship, submit a PhD application using our online application system [www.bristol.ac.uk/pg-howtoapply]

Please ensure that in the Funding section you tick “I would like to be considered for a funding award from the Civil Engineering or Engineering Mathematics Department” and specify the title of the scholarship in the “other” box.

Candidate requirements: 

The candidate must hold/achieve a minimum of a master’s degree (or international equivalent) in a science, mathematics or engineering discipline.  Applicants should have knowledge of linear algebra, regression techniques, and some knowledge of optimisation methods and should know how to program in at least one high level or scripting language (e.g. Python, R, MATLAB).

This project would be best suited to students with expertise in Civil Engineering or Data Science/Machine Learning.

If English is not your first language, you need to meet this profile level:

Profile E

Further information about English language requirements and profile levels.

Funding:

Available for UK/EU students (UK settled status) with permanent UK residency covering tuition fees (at the UK student rate) and a tax-free stipend for 3.5 years plus a travel/consumables budget.

For eligibility and residence requirements please check the UKRI UK Research and Innovation website.

Contacts:  

For questions about eligibility and the application process please contact CAME Postgraduate Research Admissions 

Advert information