PhD Research Project

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Software and hardware integration in tackling global food fraud and food processing problems

Institution:

Queen’s University Belfast

Dept/School/Faculty:

School of Biological Sciences

PhD Supervisor:

Dr T Koidis

Co-Supervisor:

Dr J Martinez del Rincon

Application Deadline:

No more applications being accepted

Funding Availability:

Funded PhD Project (European/UK Students Only)

PhD Research Project

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In the current scene of global food supply and production, it is becoming increasingly challenging to detect sophisticated fraud, to tackle food processing problems and to meet consumers' elevated requirements of quality and safety. There is therefore a need to develop intelligent information systems, based on machine learning, artificial intelligence and pattern recognition, as well as integrating software and hardware in solving some key food science related problems such as detecting adulteration and geographical origin (e.g. oils) and automating food process control.

Current methods to authenticate foods are based on laboratory analyses or processing control, which requires heavy and expensive instruments or manual labour. By applying pattern recognition methods, food properties can be estimated accurately under complex scenarios, which would otherwise require time-consuming and often expensive analytical testing. In this project we aim to explore the applicability of signal processing and pattern recognition techniques in order to develop software useful in tackling food authenticity, safety and security problems. Moreover, mobile technology has yet to find its way in areas like food processing and control, which creates even more opportunities if appropriate software is embedded into low-cost mobile devices.
Some outcomes to be explored in this PhD are: a) software tools that help with calibration and analysis of complex chromatography, spectroscopic and other signals to verify authenticity of specific foods, based on machine learning and pattern recognition techniques, b) development of next generation searchable databases with food authenticity data to fight global food fraud, c) the proof-of-concept use of low-cost mobile computer in food processing and processing control including decision making.

This project will be supervised by Dr Tassos Koidis of the School of Biological Sciences and Dr Jesus Martinez del Rincon of the School of Electronics, Electrical Engineering and Computer Science.

Funding Notes:

The successful applicant for this project will be awarded a DEL studentship.

If you are resident in the UK or elsewhere in the EU, it is STRONGLY RECOMMENDED that you refer to the terms and conditions of DEL postgraduate studentships (http://go.qub.ac.uk/delterms) to ascertain whether you are eligible for a studentship covering fees and maintenance or a studentship covering fees only.

Please note that non-EU residents are NOT ELIGIBLE for DEL studentships.