Research Fellow in AI-based Phenotyping

Fixed Term Contract for 2.5 years on a Full-time basis. Part-time (pro rata) will be considered.

Full-time starting salary is normally in the range of £37,337 per annum

We welcome applications from passionate plant science researchers, bioinformaticians or remote sensing/data scientists with skills in image processing or phenotyping with a collegiate and self-driven attitude towards multidisciplinary research.

About the Role

The role includes carrying out fundamental plant science research related to a high-profile BBSRC-funded project on potato dormancy, with PepsiCo International Limited and Solynta UK as industrial partners.

You will be:

1. i) Developing a non-destructive rapid AI-based imaging system to assess potato dormancy break, including: data collection, processing, AI model development and classification accuracy assessment.
2. ii) Involved in supporting an electrophysiology-based machine learning model to predict dormancy break.

You will be part of a multidisciplinary academic and industry team of plant molecular biologists, geneticists, postharvest physiologists, agronomists, bioinformaticians, and specialist technicians in postharvest technology, analytical chemistry and cell culture. The project’s broad vision is to create an agricultural system for potatoes that is sustainable and economically viable. For that, we aim to extend potato storage through elucidating the molecular and physiological mechanisms that govern dormancy break. Overall, you will contribute to reducing food waste, and reducing the energy and greenhouse gas emissions associated with cold storage of tubers.  

About You

You will be educated to doctoral level in remote sensing, agricultural engineering, geospatial science, bioinformatics (or similar relevant subject) and have research experience in plant science. With excellent communication skills, you will have expertise in designing and undertaking glasshouse, field and/or crop trials. You will have proven experience in image processing, AI-image classification, data analysis and interpretation, related to plants and/or soil.

About Us

As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here.

The project will be part of the Environment and Agrifood Theme with a strong track record in soil, crop and plant sciences, including postharvest biology and technology, and plant molecular biology.

Our Values and Commitments

Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here.

We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity Working Families. Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here.

Working Arrangements

Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners.

How to apply                                    

For an informal discussion about this opportunity, please contact Dr Toby Waine, Reader in Applied Remote Sensing (t.w.waine@cranfield.ac.uk).

Closing date for receipt of applications:  22 June 2025

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