Postdoc position – Self-Supervised Learning for Image-Based Phenotyping

Future food systems urgently need new crops that deliver sustainability, nutrition, and resilience. This includes crops that support the protein transition and thrive under changing climates while staying within planetary boundaries. However, breeding progress on key traits, such as yield stability and drought tolerance, remains too slow to meet accelerating agricultural pressures. These traits are governed by complex genetic architectures and strong environmental interactions, making rapid improvement particularly challenging.

Digital phenotyping offers a transformative opportunity to accelerate crop improvement. Drones, satellites, and high-throughput sensors now generate large-scale, multi-temporal image data at single-plant resolution, capturing subtle variation in growth, stress responses, and yield components that conventional approaches cannot detect. The key challenge is no longer data collection but transforming these vast and complex datasets into actionable insights for advanced breeding.

In this context, the PHENOM project aspires to develop next-generation AI methods for plant phenotyping. The project focuses on self-supervised foundation models that learn biologically meaningful representations from plant images. Such models generate embeddings that could capture genetic variation, environmental responses, and their interactions, forming a new digital layer for phenotyping that goes beyond traditional statistical approaches.

As a postdoctoral researcher, you will design and develop self-supervised learning approaches for large-scale, multi-temporal plant image datasets. You will work on extracting robust and interpretable representations of plant traits, enabling more precise phenotyping and supporting predictive breeding pipelines. 

You will work with quinoa as both a model and target crop—a resilient, protein-rich species suited to sustainable agriculture. The project is a collaboration between Radicle Crops and Wageningen University, combining extensive UAV datasets, real-world breeding pipelines, and world-leading expertise in agricultural AI. Together, the partners build an end-to-end pipeline from data curation and model development to validation in practical breeding applications. 

Your duties and responsibilities include: 

• Conduct research on state-of-the-art self-supervised learning and foundation models for plant phenotyping.
• Develop models for extracting meaningful representations from large-scale, multi-temporal plant image datasets.
• Disseminate your research through high-impact publications and presentations at leading AI and plant science conferences.
• Collaborate with interdisciplinary partners to integrate your methods into practical breeding pipelines.                 

You will work here

The research is embedded within the chair Artificial Intelligence which is led by Prof. Ioannis Athanasiadis. You will be co-supervised by Prof. Ricardo da Silva Torres and Prof. Ioannis Athanasiadis.

This position is part of the Academic Career Framework (ACF) at Wageningen University & Research.

You are highly motivated, self-driven, and curious to advance use-inspired artificial intelligence methods to accelerate crop improvement. You have a strong intrinsic motivation for "AI for Good," driven by a desire to apply rigorous machine learning to pressing climate challenges. You bring along your enthusiasm to work in a highly dynamic, international team towards the common objective of building trustworthy, high-impact environmental intelligence.

You also possess: 

• A successfully completed PhD degree in artificial intelligence, computer science, statistics, engineering, or a similar relevant field.
• Demonstrated experience in applied machine learning. A background or interest in machine learning, computer vision, or time-series analysis is desirable. Experience with plant breeding or self-supervised learning is a strong plus.
• Proficiency in programming in Python and experience with PyTorch, Scikit-Learn, or related modern machine learning libraries. Familiarity with collaborative coding environments (e.g., Git) and working on high-performance computing (HPC) clusters is an advantage.
• Good scientific writing and communication skills, as demonstrated by your thesis report or contributions to scientific papers.

For this position your command of the English language is expected to be at C1 level. Sometimes it is necessary to submit an internationally recognized Certificate of Proficiency in the English Language. More information can be found here.

Wageningen University & Research offers excellent terms of employment. A few highlights from our Collective Labour Agreement include:

• sabbatical leave, study leave, and partially paid parental leave;
• working hours that can be discussed and arranged so that they allow for the best possible work-life balance;
• there is a strong focus on vitality and you can make use of the sports facilities available on campus for a small fee;
• a fixed year-end bonus of 8.3%;
• excellent pension scheme.

In addition to these first-rate employee benefits, you will of course receive a good salary. Depending on your experience, we offer a competitive gross salary of between € 3.546,- and € 5.538,- for a full-time working week of 38 hours, in accordance with the Collective Labour Agreements for Dutch Universities (CAO-NU) (scale 10). Additionally, a contract for 0.8 FTE can be discussed. We offer you a temporary contract for the duration of two years (1+1). 

We encourage development and internal mobility within our organisation. Our recruitment and selection policy sets out the conditions that apply specifically to you as a (former) employee. If you have any questions, we are happy to help.

You will work on the greenest and most innovative campus in the Netherlands, in an international and open working environment. 

Wageningen University & Research is the university and research centre for life sciences. The themes we deal with are relevant to everyone around the world and Wageningen, therefore, has a large international community and a lot to offer to international employees. 

Because we expect you to work and live in the Netherlands our team of advisors on Dutch immigration procedures will help you with the visa application procedures for yourself and, if applicable, for your family. 

Feeling welcome also has everything to do with being well informed. Wageningen University & Research's International Community page contains practical information about what we can do to support international employees coming to Wageningen. Furthermore, our Welcome Center can assist you with any additional advice and information about for example housing, opening a bank account, dual career programs or schooling. Finally, certain categories of international staff may be eligible for a tax exemption on a part of their salary during the first five years in the Netherlands.

For more information about the position, please contact Ricardo Torres, Professor, via email: ricardo.torres@wur.nl .
Questions about the procedure? Get in touch with Noorien Abbas, Corporate Recruiter, via vacaturemeldingen.psg@wur.nl

Ready to apply?
Click on the application button next to the vacancy on our website. Only applications submitted through our website will be considered.

You can apply up to and including Monday June 8th 2026. The first interviews are scheduled for Monday June 22, 2026. Internal candidates are preferred to apply before May 10th 2026.

Procedure
As part of our selection process, an assessment may be incorporated within the procedure

Welcome, safe, and valued
Wageningen University & Research (WUR) highly values diversity and inclusion because we believe that different insights lead to innovative solutions. We create a work environment where everyone feels welcome, safe, and appreciated, regardless of background, identity, or experience. Together, we are building a culture where everyone's unique contribution adds to the success of our organization.

​The mission of Wageningen University & Research is “To explore the potential of nature to improve the quality of life”. Under the banner Wageningen University & Research, Wageningen University and the specialised research institutes of the Wageningen Research Foundation have joined forces in contributing to finding solutions to important questions in the domain of healthy food and living environment. With its roughly 30 branches, 7,600 employees (6,700 fte) and 13,100 students and over 150,000 participants to WUR’s Life Long Learning, Wageningen University & Research is one of the leading organisations in its domain. The unique Wageningen approach lies in its integrated approach to issues and the collaboration between different disciplines.

Read the 5 reasons why your future colleagues enjoy working at WUR and watch the video below to get an idea of our green campus!

We will recruit for the vacancy ourselves, so no employment agencies please. However, sharing in your network is appreciated.

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