Hyperspectral Imaging and Sensor-Based Monitoring of Mineral Processing Equipment for Advanced Model Predictive Control - Mining and Minerals Engineering - EPSRC DTP funded PhD Studentship Ref: 2966

About the award

This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding.

The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students.

Please note that of the total number of projects within the competition, up to 15 studentships will be filled.

Dr Robert Fitzpatrick
Dr Weiguo Xie
Prof Hylke Glass

Penryn Campus, Cornwall

Project Description
An EPSRC funded DTP Studentship PhD project to improve security and sustainability of raw materials in the UK. The project investigates hyperspectral imaging and sensor monitoring of mineral processing equipment for advanced model predictive control.

The UK is a prosperous country with a highly developed economy. However, there is a lack of raw materials to feed manufacturing sectors leading to a high reliance on importation. The ethics and sustainability as well as the security of these raw material supplies is an important issue for the UK.

To help address these issues it is important to improve the viability of UK and EU sources of natural resources. One way to achieve this is to increase levels of automation in the processing of minerals. Hyperspectral imaging is gaining traction in the exploration of mineral deposits and for pre-concentration. However, there is little use of this technology within processing plants…

The aim of this PhD is to devise and investigate suitable means of implementing hyperspectral imaging and sensor-based monitoring into mineral processing plants, with a specific focus on gravity separation equipment. The data obtained will be implemented into an advanced model predictive control system.

The student will characterise minerals using a range of scientific equipment including X-ray fluorescence analysers, Near infrared and raman spectrometers. The results of the characterisation will be used to inform the implementation of relatively low-cost sensors for monitoring mineral process equipment. Work will include physical experimentation on lab-scale mineral processing equipment and on-site implementation of sensors into industrial facilities and/or advanced small-scale continuous processing plants in the UK and Europe. Students will undertake data analysis of hyperspectral data and create advanced model predictive control systems.

The suitable candidate will have at least a 2:1 degree in geology, physics or a relevant engineering subject. Ideally the candidate will have experience of one or more of: Mineral processing, process control or analysis of spectral data. 3.5 Year PhD scholarship.

Entry Requirements
You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in Physics, any relevant engineering discipline, Geology, Mining Engineering. Experience in minerals engineering, process control and/or hyperspectral data analysis is desirable.

If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information and a list of acceptable alternative tests.

The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes.  If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU.  For information on EPSRC residency criteria click here.

Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database for alternative options.


Application deadline:10th January 2018
Value:3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year.
Duration of award:per year
Contact: Doctoral Collegepgrenquiries@exeter.ac.uk

How to apply

You will be required to upload the following documents:
•       CV
•       Letter of application outlining your academic interests, prior research experience and reasons for wishing to
        undertake the project.
•       Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim
        transcript if you are still studying.
•       If you are not a national of a majority English-speaking country you will need to submit evidence of your current
        proficiency in English.  For further details of the University’s English language requirements please see

The closing date for applications is midnight (GMT) on Wednesday 10 January 2018.  Interviews will be held at the University of Exeter in late February 2018.

If you have any general enquiries about the application process please email: pgrenquiries@exeter.ac.uk.
Project-specific queries should be directed to the supervisor.

During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

• the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
• administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.