PhD PROJECT IN USING COMPUTER VISION TO MONITOR WATER QUALITY BY ANALYSING COMPLEX PARTICULATES

Water quality surveillance is vital for sectors like oil and gas, waste management, and environmental marine management. Current manual sampling and laboratory analysis are expensive and lack real-time analytics. In-line measurement approaches provide real-time evaluation within systems, but existing automated edge technologies are limited to specific parameters like pH, temperature, and certain particulates. Detecting small biological and mineral matter in water is challenging, hindering accurate assessment in natural settings. This limitation hampers effective water quality monitoring, driving the need for real-time in-line systems.

To address these challenges, this project will explore novel microscopy systems, autonomous onboard spectral sensing, and AI analysis technology. Overall, the project aims to develop lightweight computer vision models for real-time deployment in water analysis systems. The project will make novel contributions to the area of artificial intelligence and specifically computer vision.

Objectives:
The focus of the project will be to develop novel artificial intelligence methods with the following specific objectives:
– Develop novel, multi-modal, computer vision models to analyse complex particulates captured with digital holographic microscopy and integrate spectral measurements.
– Develop novel partnership learning methods, inspired by Federated learning [2], to share knowledge across different imaging modalities with a shared goal.
– Refine the developed modelling solutions and assess their efficacy for in-line water sample analysis.

This project is in partnership with Inov8 Systems Ltd. The successful applicant will have the opportunity to spend extended periods in the company using the excellent equipment base and, more importantly, working with the highly experienced company personnel. The students’ training in the company will be based on direct and hands-on experience of working in an industrial research and innovation environment focused on developing industry-leading measurement products.

[1] Melanthota, Sindhoora Kaniyala, et al. “Deep learning-based image processing in optical microscopy.” Biophysical Reviews (2022): 1-19.

[2] Li, Tian, et al. “Federated learning: Challenges, methods, and future directions.” IEEE Signal Processing Magazine 37.3 (2020): 50-60.

Funding Information

To be eligible for consideration for an EPSRC Studentship (covering tuition fees and maintenance stipend of approx. £18,622 per annum), a candidate must satisfy all the eligibility criteria based on nationality, residency and academic qualifications.

Funding Eligibility:
Please note that funding is only available to candidates who qualify as a ‘Home’ student. To be classed as a Home student, candidates must meet the following criteria and the associated residency requirements:
• Be a UK National,
or • Have settled status,
or • Have pre-settled status,
or • Have indefinite leave to remain or enter the UK.
Candidates from ROI may also qualify for funding.

Academic Requirements:
The minimum academic requirement for admission is normally an Upper Second Class Honours degree from a UK or ROI Higher Education provider in a relevant discipline, or an equivalent qualification acceptable to the University.

COURSE CONTENT

Research Information

Associated Research
Research within the School is organised into research themes combining strengths by working together on major projects, in many cases in collaboration with key technology companies.
ECIT brings together internationally recognised research groups specialising in key areas of advanced digital and communications technology.

PhD Opportunities
PhD Opportunities are available in a wide range of computer science subjects, aligned to the specific expertise of our PhD supervisors.

Research Impact
Queen’s is a leader in commercial impact and one of the five highest performing universities in the UK for intellectual property commercialisation. We have created over 80 spin-out companies. Three of these –
Kainos, Andor Technology and Fusion Antibodies – have been publicly listed on the London Stock Exchange.

Research Projects
Queen’s has strong collaborative links with industry in Northern Ireland, and internationally. It has a strong funding track record with EPSRC and the EC H2020 programme.

Research Success
The research profile produced by the 2014 UK Research Excellence Framework (REF) graded 80 per cent of our research activity as ‘world-leading’ or ‘internationally excellent’, confirming the School’s reputation as an internationally-leading department.

Career Prospects

Introduction
For further information on career opportunities at PhD level please contact the Faculty of Engineering and Physical Sciences Student Recruitment Team on askEPS@qub.ac.uk. Our advisors – in consultation with the School – will be happy to provide further information on your research area, possible career prospects and your research application.

ENTRANCE REQUIREMENTS

Graduate
The minimum academic requirement for admission to a research degree programme is normally an Upper Second Class Honours degree from a UK or ROI HE provider, or an equivalent qualification acceptable to the University. Further information can be obtained by contacting the School.

International Students

For information on international qualification equivalents, please check the specific information for your country.

English Language Requirements

Evidence of an IELTS* score of 6.0, with not less than 5.5 in any component or equivalent qualification acceptable to the University is required (*taken within the last 2 years).

International students wishing to apply to Queen’s University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.