Elsewhere on Ulster
This project is funded by:
FibreWatch tackles sustainability in fibre crop production by the use drones, sensors, and AI to monitor flax and hemp fields, mapping plant health, soil moisture and nutrient status. Hemp grows rapidly and can capture substantial CO₂ in its biomass, yet typically requires very low fertilizer and pesticide inputs. Flax also fits this model: it is often grown in rotation, needs little to no irrigation or chemicals, and its entire stalk is used. This data-driven approach helps farmers reduce water and fertilizer use, lowering emissions and improving yields. Working with UK and US teams, you’ll build “digital twins” to test management strategies before going to the field. Through this hands-on project, the student will apply drone imaging, AI analytics, and simulation tools to support more sustainable and circular agriculture. They will collaborate with farmers, engineers, and policy experts to create solutions that improve on-farm decision-making and supply chain traceability. The project offers a unique opportunity to develop interdisciplinary skills in agri-tech, environmental science, transport systems, and data analysis while contributing to real-world climate resilience in rural communities. Ideal candidates will have a passion for sustainability and innovation and an interest in applying technology to solve pressing agricultural and environmental challenges. The project includes an international visit to the partner, Texas A&M Transportation Institute (TTI), where the PhD researcher will analyse the carbon footprint of transporting fibre crops from farm to processing facilities. This unique collaboration combines agricultural data with transport emissions modelling, linking the sustainability of farming systems with cleaner logistics and supply chains. It strengthens UK–US research cooperation and offers the student valuable global experience working with world-leading experts in sustainable mobility and environmental systems. |
Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.
We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.
In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.
If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.
The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.
Appointment will be made on merit.
This project is funded by:
This scholarship will cover tuition fees and provide a maintenance allowance of £21,000* (tbc) per annum for three years (subject to satisfactory academic performance). A Research Training Support Grant (RTSG) of approximately £900 per annum is also available.
To be eligible for these scholarships, applicants must meet the following criteria:
Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme.
Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.
Due consideration should be given to financing your studies.
*Part time PhD scholarships may be available, based on 0.5 of the full time rate, and will require a six year registration period
| Serrano, T., Brym, Z. T., Monserrate, L. A., Her, Y. G.,
Stanford, J., Bhadha, J. H., Singh, H., Sharma, L. K., Upadhyaya, Y. R.,
Griffin, W. D., & Shellenbarger, H. T. (2025). Nitrogen Fertilizer
Effects on Hemp Biomass Production Detected by Drone-based Spectral Imaging.
HortScience, 60(3), 353–361. Pankaj Pal, Juan Landivar-Bowles, Jose Landivar-Scott, Nick Duffield, Kevin Nowka, Jinha Jung, Anjin Chang, Kiju Lee, Lei Zhao, Mahendra Bhandari, Unmanned aerial system and machine learning driven Digital-Twin framework for in-season cotton growth forecasting, Computers and Electronics in Agriculture, Volume 228, 2025, 109589, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2024.109589. All-Ireland Sustainability, “Flax in Sustainable Farming and Decarbonisation,” AllIrelandSustainability.com |
Submission deadline
Friday 27 February 2026
04:00PM
Interview Date
March 2026
Preferred student start date
14th September 2026
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