We are looking for candidates who should have (or expect to achieve) a minimum of a 2.1 Honours degree in a relevant subject area related to biological sciences, computer science or agriculture, with an interest in working across disciplines. Applicants with a minimum of a 2.2 Honours degree will be considered providing they have a Masters degree or significant relevant outputs/experience, such as publications.
Project outline
Cereal grains provide a large portion of our food, either for direct consumption or indirectly via brewing or animal feed. Composition varies between and within varieties and is affected by environmental stress. Composition largely determines end use and value to the producer. The grain is a composite structure, with three genetically distinct individuals, the embryo, endosperm and maternal protective tissues. Loss of spatial / developmental information during typical destructive compositional analysis means we don’t fully understand how composition is controlled. This project aims to develop automated non-destructive tools, combining state of the art imaging with spatial molecular analyses, genetics and deep learning (AI) to model (see Fig for example AI model – embryo in red, endosperm in green) and extract novel information that could be used for crop improvement and understanding the effect of climate change on grain quality.
The project is based on the exciting development of novel methods to image and dissect tissues in QUB (iKnife) and Aberystwyth (CT and hyperspectral scanning). The challenge is to combine these different data streams and extract meaningful information in a systematic manner that useful to researchers, breeders and agriculture.
Training
In this interdisciplinary project, the student will work with plant geneticists at Aberystwyth, medical biochemists at Queens, Belfast and computer scientists in Aberystwyth Computer Science Dept. You will learn a range of specialist bio-medical imaging skills, including the use of high resolution cameras and microscopes, and innovative metabolite analysis equipment, and combine this with computer vision skills to apply deep-learning algorisms to co-register (line up) different datastreams, explore and exploit the data. Also, Aberystwyth University retains a strong public-good plant breeding program, so you will have the opportunity to work closely with breeders and be trained in crop genetics, including specialist software for QTL analysis and GWAS. Plant Breeding has been identified as a major skill-gap in the UK and has excellent career opportunities, particularly when combined with new ways of collecting and handling large datasets. Collaborative supervision from the QUB provides training opportunities in advanced biomolecular science and there will be the opportunity to visit other centers working on grain biodiversity, such as John Innes. There may also be opportunities to spend time at other major plant phenotyping centres in Europe, Australia or North America, particularly Canada where we have a collaboration with the synchrotron at Saskatoon.
How to Apply
Applications will be by an online application form only. Do not send CVs.. Please go to the FoodBioSystems website to see guidance to applicants, information on academic and funding eligibility and language proficiency.
We will be holding an online information meeting for applicants on 11 January 2023. More information and joining instructions will be shared on the FoodBioSystems website.
Equality Diversity and Inclusion:
The FoodBioSystems DTP is committed to equality, diversity and inclusion (EDI), to building a doctoral researcher (DR) and staff body that reflects the diversity of society, and to encourage applications from under-represented and disadvantaged groups. Our actions to promote diversity and inclusion are detailed on the FoodBioSystemsDTP website.