PhD Studentship: Statistical Techniques for Engineering with Advanced Materials (STEAM)

Newcastle University - School of Mathematics, Statistics and Physics

Value of award: 100% tuition fees, a tax-free stipend of (up to) £14,553 pa (17/18 level, subject to minor change), a desktop computer, and £1500 travel allowance.
Start date and duration: September 2018. for 3.5 years.

Overview

The next decade will see step changes in data-driven technology, impacting all aspects of engineering and industry. The emergence of manufacturing protocols for 3D printed stainless steel promises a dramatic increase in the ambition and complexity of structures that can be designed and built. However, at the same time these techniques raise urgent statistical challenges which must first be addressed.

On the microscale, the inherent variability of advanced printed materials is such that their basic material properties are in effect random, and this variation not yet well-characterised. On the macroscale, how manufacturing standards and safety guarantees can be provided in the context of an uncertain material is yet to be determined.  Moreover, it is unclear how inspection and continued monitoring of these structures should be performed.

This project, a joint venture between the Lloyds-Turing programme on data-centric engineering at the Alan Turing Institute, Imperial College London and Newcastle University, brings together experts in material testing, engineering, statistics and mathematics so that these urgent questions can be addressed. Detailed experiments are being performed to probe the material properties of 3D printed stainless steel and these data will be analysed with novel statistical methods, to be developed, in order to provide important insight into novel advanced material.

We are offering a PhD Studentship in the School of Mathematics, Statistics and Physics at Newcastle University to work on this project. The student will benefit from a year-long placement at the Alan Turing Institute, London, envisaged to take place in the second year.

Further information on the STEAM project can be found at http://oates.work/steam.

Sponsor: School of Mathematics, Statistics and Physics, Newcastle University.
Name of supervisor(s): Dr Chris Oates

Eligibility Criteria

This studentship is available to UK/EU and International candidates, who have/expect a 2:1 honours degree in computing science, mathematics, statistics or another strongly quantitative discipline, or an international equivalent.

Applicants whose first language is not English require a minimum of IELTS 6.5. International applicants may require an ATAS (Academic Technology Approval Scheme) clearance certificate prior to obtaining their visa and to study on this programme.

How to apply

You must apply through the University’s online postgraduate application system. To do this please ‘Create a new account’.

All relevant fields should be completed, but fields marked with a red asterisk must to be completed. The following information will help us to process your application. You will need to:

  • insert the programme code 8080F in the programme of study section
  • select 2017/2018 for Academic Year
  • select ‘PhD Mathematics and Statistics (FT) - Statistics’ as the programme of study
  • insert the studentship code MSP001 in the studentship/partnership reference field.

Contact: Please email Dr Chris Oates for further information.

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Type / Role:

PhD

Location(s):

Northern England