An integrated machine learning based hyperspectral imaging technique for detection and localisation of objects

Robert Gordon University, through School of Engineering is offering a tuition Fees only fulltime PhD studentship for a home or an overseas candidate.  

This proposed research aims to integrate machine learning with hyperspectral imaging and will be delivered within the Instrumentation & Sensors Research Group.

Hyperspectral imaging, also referred to as spectroscopy, has applications in biomedicine, oil and gas, landmines detection, agriculture, defence, space, forestry, and power industry. The Hyperspectral imaging technique captures the radiated electromagnetic signals from visible to infrared wavelength in very harsh industrial conditions. Remote and autonomous sensing for detection and localisation of objects and condition monitoring has emerged as a growing interest for researchers. 

For example, ubiquitous and continuous monitoring of high voltage systems can be seen as possible by continuously capturing the image by high definition camera, spectroscope, or using drones and interpreting the information into meaningful object detection by pattern recognition. 

On the other hand, machine learning has emerged as a highly plausible tool with substantial predictive power that utilises predictive algorithms. The integration of machine learning with hyperspectral imaging can solve many challenges, especially under harsh industrial conditions.  

Applications should be emailed to Dr Umar F Khan at [Email Address Removed] The applications should consist of a covering letter or personal statement of interest, and a CV.

Deadline for receipt of applications is 31 July 2021.

It is expected that candidates are available to register and commence study on 01 Feb 2022.

Questions should initially be addressed to: 

Dr Umar F Khan

School of Engineering

Robert Gordon University

Riverside East, Garthdee Campus

Aberdeen, AB10 7GJ

United Kingdom

E: [Email Address Removed]

W:www.rgu.ac.uk

Entry Requirements

Applicants should have a First- or Second-Class UK honours degree, or equivalent, in a relevant discipline such Electrical/Electronic Engineering or Computer Science. An MSc in a relevant subject is highly desirable. Proficiency in MATLAB is required.

Please see further information available at: http://www.rgu.ac.uk/research/graduate-schools/applying-for-a-research-degree/funded-studentship-opportunities.