| Location: | Edinburgh |
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| Salary: | £41,064 to £48,822 per annum (Grade 7) |
| Hours: | Full Time |
| Contract Type: | Fixed-Term/Contract |
| Placed On: | 10th September 2026 |
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| Closes: | 1st October 2026 |
| Job Ref: | 14891 |
Full Time: 35 hours per week
Fixed term: for 24 months (there may be the opportunity to extend to 30 months TBC)
The Opportunity:
We are seeking a Postdoctoral Research Fellow in Applied Artificial Intelligence for the recently established TEAM-AI project: Tools for Evaluating and Advancing Meaningful AI Adoption in Public Breeding Programmes, a global partnership between the Roslin Institute and CGIAR, including CIMMYT and National Agricultural Research Systems (NARES). In this role, you will develop and evaluate innovative artificial intelligence approaches to support public plant breeding. Working with large-scale genomic, phenotypic, environmental, and field trial datasets, you will benchmark AI and quantitative genetics methods, develop multimodal and hybrid modelling frameworks, and investigate explainable AI strategies to improve prediction, interpretability, and breeding decision-making.
Join TEAM-AI to translate cutting-edge analytics into practical solutions for global food security.
TEAM-AI aims to ensure that advances in AI and data science deliver meaningful benefits for public breeding programmes and the farmers they target. This role offers a unique opportunity to combine expertise in biometrics, quantitative genetics and software development to address real-world challenges in agriculture. Working closely with CGIAR and NARES partners through collaborative visits, workshops and training activities, you will gain experience with public breeding programmes operating across diverse environments. The resulting tools and resources will be deployed across CGIAR and NARES programmes, helping breeders make more informed and representative decisions, accelerate crop improvement, and strengthen food security and climate resilience across the Global South.
The successful candidate will join the Biometrics for Breeding Group at Roslin, who develop statistical and quantitative genetic methods for improving the productivity and sustainability of breeding programmes amid a changing climate. We offer exciting opportunities to build an international network spanning academia, industry and public breeding programmes, while contributing to capacity building in AI-enabled breeding at Roslin and expanding our suite of data-driven breeding resources and tools.
This post is full-time (35 hours per week) on-campus working; however, we are open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
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