Postgraduate research opportunities Portable AI-driven imaging flow cytometry system for mastitis detection & antimicrobial stewardship in dairy farms
ApplyKey facts
- Opens: Thursday 26 March 2026
- Deadline: Friday 17 April 2026
- Number of places: 1
- Duration: 4 years
- Funding: Equipment costs, Home fee, Stipend
Overview
This PhD project places artificial intelligence and computational modelling at the heart of next-generation mastitis diagnostics for sustainable dairy farming. Rather than focusing primarily on hardware development, the research targets the core scientific challenge: how to extract clinically meaningful information from complex optical data using advanced machine learning.Eligibility
We are looking for you to have a a minimum first class or 2:1 Bachelor's degree or MSc with merit in a relevant subject area.
You must have Home fee status. If you are a non-native English speaker you must hold a minimum qualification equivalent to IELTs 6.5. A Bachelors or Masters degree from an English-speaking University will also be considered. You must also be resident in the UK for the majority of your studies and any time spent overseas should be for the purposes of fieldwork/long-term attachment.
Please note, the SUSTAIN Team cannot assess your eligibility for home-fees status, and submitting an incorrect fee classification may result in a studentship offer being withdrawn.
Project Details
Mastitis remains the most common and costly disease in dairy cattle, driving significant antimicrobial use (AMU). Rapid, accurate on-farm diagnostics are essential to enable targeted treatment and reduce unnecessary antibiotics. While imaging flow cytometry and microfluidic platforms are now mature and can be implemented using modular, plug-and-play engineering solutions, the real bottleneck lies in robust, generalisable algorithms capable of interpreting high-dimensional image data under real-world farm conditions.
You will develop advanced deep learning models to classify milk samples from healthy and infected cows, differentiating pathogen types directly from image streams. A central innovation will be the exploitation of diffraction-informed features to detect and classify bacteria that are near or below optical resolution limits.
A comprehensive, well-annotated digital library of milk images will be constructed, supported by access to isolated bacterial strains through collaboration with the ASTB Ltd. The developed algorithms will be benchmarked against existing biochemical and PCR-based diagnostic methods used on farms.
You will gain strong expertise in machine learning, computational imaging, uncertainty quantification, and applied AI in agriculture, contributing to reduced antimicrobial overuse and advancing sustainable, data-driven dairy systems.
Further information
This 4-year PhD programme is under the UKRI AI Centre for Doctoral Training in Sustainable Understandable agri-food Systems Transformed by Artificial Intelligence (SUSTAIN). SUSTAIN is a collaboration between the Universities of Lincoln, Aberdeen, Queen’s Belfast and Strathclyde, and focuses on the application of Artificial Intelligence (AI) to sustainable agri-foxlod. Academic staff and partners have co-created projects based on key industry challenges, which will be shaped with your input during the first year of your PhD. All projects will benefit from external partner involvement. Recruitment is being co-ordinated by the University of Lincoln.
Funding details
4-year fully funded studentship funded by UK Research and Innovation (UKRI). All PhD tuition fees paid. A tax-free stipend at UKRI rates to cover living costs. A Research Training Support Grant (RTSG) of £3,000 each year to support travel, training and consumables costs (up to £12,000 in total). Additional funding to support outreach and dissemination, attendance at summer schools, research events, and development projects. This year, the SUSTAIN CDT has been invited to participate in the TechExpert pilot, which provides an enhanced stipend for Home students of £10,000 above the UKRI minimum. This is only available for students starting in October 2026.
While there is no funding in place for opportunities marked "unfunded", there are lots of different options to help you fund postgraduate research. Visit funding your postgraduate research for links to government grants, research councils funding and more, that could be available.
Supervisors
Additional Supervisors: Dr Simon Cameron, Queen's University Belfast, Andrew Smith, ABC Dairy Ltd / ASTB Ltd and Treenie Bowser, The Dairy Vet Ltd / ASTB Ltd
Apply
If you are interested, please apply via SUSTAIN CDT.
The SUSTAIN Admissions Committee and Project Teams will evaluate your application based on the SUSTAIN Skills Matrix to shortlist and select successful candidates.
If you are selected for interview, you will need to give a presentation explaining your interest in your selected project(s) and SUSTAIN. Your presentation will be evaluated based on the following criteria:
- subject knowledge
- communication skills
- industry knowledge
Number of places: 1
Shortlisting will take place week commencing 4 May 2026, with interviews taking place online between 19 May and 2 June 2026. Candidates will be informed week commencing 9 June 2026. Thereafter, the successful candidate will then complete and submit their application to the University of Strathclyde.
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