PhD in AI for Plant Breeding — Wageningen University

Key details

• Host institution: Wageningen University & Research
• Location: Wageningen University & Research, Droevendaalsesteeg, Wageningen, Netherlands
• Application deadline: June 8, 2026

Funding

Not funded by a EU programme

Funding level (from listing): partial or not via EU framework — confirm on the official call.

How to apply

• Apply by email to [email protected] (subject line and attachments per the official instructions).
• Full vacancy text and updates: Euraxess listing.

About the position

We are looking for a PhD candidate to help shape the future of plant breeding by combining machine learning, multi-omic data analyses, genetics, and cutting-edge phenotyping to discover the molecular drivers of complex traits.

Project background

Most traits behind crop performance and environmental responses are complex, driven by many interacting genes. These have classically been studied using genome-wide association studies (GWAS) and other linear approaches. Recent developments in machine learning and AI have opened new avenues for studying the genetic architecture and molecular underpinning of complex traits. Building interpretable and explainable AI models allows for not only improved trait prediction but also understanding how predictions were made, providing new insights into the underlying biological processes.

Key task

Build AI models linking different levels of biological complexity to gain novel insights into underlying gene and molecular networks. Initially, the focus will be on integrating transcriptome, proteome, and metabolome profiles measured at the single-cell level in faba bean to understand the signatures and drivers of differences between cell types and linking them to observed plant traits.

Your duties and responsibilities

• Design and implement methods to link genotypic and phenotypic data across different scales, from single cells (multi-omics) to whole plants (high-throughput phenotyping)
• Design and implement interpretable and biologically grounded AI-based models to predict molecular and whole-plant phenotypes using multimodal datasets
• Use the newly developed methods to study the genetic architecture of complex traits across different scales of biological complexity
• Benchmark newly developed methods against more established techniques such as genome-wide association studies (GWAS/eGWAS)
• Work closely with colleagues across fields including bioinformatics, molecular biology, plant development, and stress responses
• Publish your findings in scientific journals, collaborate across departments and chair groups, and communicate your results in your PhD thesis and broader outreach activities

Where you will work

The research is embedded within the Wageningen University Department of Plant Breeding, with collaboration from Aarhus University Department of Molecular Biology and Genetics, Wageningen Plant Research, and other chairs of Wageningen University Plant Sciences Group. Supervision of the PhD will be led by Prof. Agnieszka Golicz, a newly appointed Chair of Plant Breeding.