University of Leeds Featured PhD Programmes
Norwich Research Park Featured PhD Programmes
Norwich Research Park Featured PhD Programmes
FindA University Ltd Featured PhD Programmes
The Hong Kong Polytechnic University Featured PhD Programmes

PhD Studentship: Deep Learning for Detecting and Analysing Defects on Surfaces

  • Full or part time
  • Application Deadline
    Monday, October 21, 2019
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Application details

Reference number: CO/GC-CDT/2020
Start date of studentship: 1 January 2020
Closing date of advert: 21 October 2019
Interview date: To be arranged

Supervisors:
Primary supervisor: Dr Georgina Cosma
Secondary supervisor: To be confirmed

Loughborough University

Loughborough University is a top-10 UK university, consistently ranked by the Guardian and other league tables. Founded in 1974, the Department of Computer has been ranked 4th in the UK for Computer Science and Information Systems (Guardian University Guide 2018) and has an excellent research track record in A.I, machine learning, data science, deep learning, robotics and computer vision.

Full Project Detail

Carrying out inspections in hard to reach places is time consuming and poses safety hazards to workers. Drones can help carry out automatic inspections faster than manual inspections by gathering data which can be automatically analysed for decision making.
The aim of this project is to create Deep Learning inspection models which can detect and classify a variety of defects in objects found in high-definition images captured by drones or by other means.

This project involves the development of custom deep learning and other algorithms for detection, analysis, classification and evaluation of defects on surfaces. The project has been defined by a company which will provide data and access to facilities for testing the deep learning models.

Experience in image processing, computer vision, and experience in implementing Deep Learning algorithms for object detection and segmentation are essential. In addition, experience in computer vision imaging-based automatic inspection and a background in engineering are highly desirable.

The ideal student will be a fast learner, self-driven, hard-working, keen to embrace the project, deliver it successfully, and should be comfortable working with deadlines. The student should be a strong programmer (using the Python programming language), have experience working with large data and be able to analyse and interpret results from experiments.

The PhD student will be based at the Department of Computer Science at Loughborough University. The student will be supervised by Dr Cosma who has experience in data science and A.I, and by industry supervisors with expertise in inspections, modelling and analysis. The student will closely work with other software engineers, and inspection experts in the project team. The student will have access to a range of training, research support and computing facilities including HPC, and high-spec machines suitable for deep learning and machine vision tasks.

Find out more:
Dr Georgina Cosma
Email:

Entry requirements

Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Computer Science or a Computer Science subject. A relevant Master’s degree and/or experience in one or more of the following subjects will be an advantage: Deep Learning, Artificial Intelligence, Data Science, and Machine Vision.

Contact details

Name: Dr Georgina Cosma
Email address:

How to apply

Applications should be made online at http://www.lboro.ac.uk/study/apply/research/. Under programme name, select Computer Science.

Please quote reference number: CO/GC-CDT/2020.

Funding Notes

The 3-year studentship will provide a tax-free stipend of £15,009 per year, plus tuition fees at the UK/EU rate (currently £4,327 per year). Whilst we welcome applications from non-EU nationals, please be advised that it will only be possible to fund the tuition fees at the international rate and no stipend will be available.

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.