University of Lincoln RIF Studentships 2014
PROJECT DETAILS
Project Title
Machine Learning for Food Quality Inspection
Project Reference
RIF2014S-44
Project Summary
A PhD position is available to join an inter-disciplinary research project at the School
of Computer Science and the National Centre of Food Manufacturing at the
University of Lincoln.
The project will investigate machine learning and computer vision techniques for the
application of food quality inspection. The research will focus on the emerging theory
of Deep Learning, which is an unsupervised technique for learning useful
representations from data.
In particular the project will investigate the application of Deep Learning to food
quality inspection of products like beans, potatoes, rice, wheat etc. based on image
analysis techniques.
Food security has been targeted as an emerging research area from both UK and
European funding bodies. The University of Lincoln has already pioneered research
in food technology. The project will advance the state-of-the-art because, in contrast
to current techniques applied to food inspection, Deep Learning is an unsupervised
learning technique and hence will enable the analysis of large volumes of food data
with little effort. It is a 'big data'-driven approach to food analysis.
The School of Computer Science at the University of Lincoln has leading expertise in
computer vision and machine learning and strong collaboration with the National
Centre for Food Manufacturing on systems development for food analysis. This
project is also in collaboration with a number of external organisations from across
the food sector.
The PhD student will work with an ambitious cross-disciplinary team and will benefit
from excellent support to produce and disseminate original research contributions.
Candidates should have a Bachelors or Masters degree in Computer Science,
Electronic Engineering, Mathematics or Physics. They should also have excellent
mathematical and coding skills (C++ and/or MATLAB). Prior experience on working
with food data is desirable but not essential.
Supervisory Team
1. Dr Georgios Tzimiropoulos, Senior Lecturer, Lincoln School of Computer
Science. http://staff.lincoln.ac.uk/gtzimiropoulos
2. Dr Grzegorz Cielniak, Senior Lecturer, Lincoln School of Computer Science.
http://staff.lincoln.ac.uk/gcielniak
3. Professor Tom Duckett , Professor of Computer Science, Lincoln School of
Computer Science. http://staff.lincoln.ac.uk/tduckett
4. Michael Dudbridge, Principal Lecturer, National Centre for Food Manufacturing.
http://staff.lincoln.ac.uk/mdudbridge
Informal Enquiries
For additional information, please contact Dr Georgios Tzimiropoulos by email with
"Machine Learning for Food Quality Inspection" in the subject line:
gtzimiropoulos@lincoln.ac.uk
Eligibility
All Candidates must satisfy the University’s minimum doctoral entry criteria for
studentships of an honours degree at Upper Second Class (2:1) or an appropriate
Masters degree or equivalent. A minimum IELTS (Academic) score of 7 (or
equivalent) is essential for candidates for whom English is not their first language.
Funded Studentships are open to both UK/EU students unless otherwise specified.
How to Apply
Please send a covering letter outlining your interest and proposed approach (up to 1
page A4) with an accompanying CV to gtzimiropoulos@lincoln.ac.uk by close of day
on 18th April 2014.
Candidates will be notified w/c 5th May of the outcome of the process and if invited to
interview, these are anticipated to take place w/c 26h May.