Ioannis N. Athanasiadis
4 months ago
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Postdoc in Self-Supervised Learning for Image-Based Phenotyping in Agriculture Wageningen University & Research in Netherlands
Degree Level
Postdoc
Field of study
Computer Science
Funding
Full-time postdoc position with a temporary contract for two years (1+1). Salary is competitive and ranges from €3,546 to €5,538 gross per month for a 38-hour week (scale 10, CAO-NU). A 0.8 FTE contract can be discussed. Additional employment benefits include sabbatical leave, study leave, partially paid parental leave, a year-end bonus of 8.3%, and an excellent pension scheme.
Deadline
Expired
Country
Netherlands
University
Wageningen University & Research
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About this position
Wageningen University & Research is recruiting a Postdoc in Self-Supervised Learning for Image-Based Phenotyping within the chair Artificial Intelligence, led by Prof. Ioannis Athanasiadis, with co-supervision by Prof. Ricardo da Silva Torres and Prof. Athanasiadis.
The project sits at the intersection of computer science, agriculture, biology, statistics, and environmental science. The research focuses on self-supervised learning, foundation models, computer vision, and image-based phenotyping for crop improvement. You will work with large-scale, multi-temporal plant image datasets, including UAV and sensor data, to learn biologically meaningful representations of plant traits, stress responses, genetic variation, and genotype-environment interactions.
The postdoc is embedded in the PHENOM project and involves collaboration between Wageningen University & Research and Radicle Crops. A key crop in the project is quinoa, used as both a model and target crop for sustainable agriculture and breeding. The role is research-intensive and aims to support predictive breeding pipelines and practical breeding applications.
Applicants should have a completed PhD in AI, computer science, statistics, engineering, or a related field, plus strong applied machine learning experience. Experience in Python, PyTorch, Scikit-Learn, Git, and HPC environments is desirable. Background in plant breeding, self-supervised learning, or time-series analysis is a plus. English proficiency at C1 level is expected.
The position offers a two-year temporary contract (1+1) with a gross monthly salary of €3,546 to €5,538 for a full-time 38-hour week, with a possible 0.8 FTE arrangement. WUR also highlights benefits such as sabbatical leave, study leave, partially paid parental leave, a year-end bonus, pension, and an international working environment in Wageningen, Netherlands.
Applications must be submitted through the WUR website only. The deadline is 8 June 2026.
Funding details
Full-time postdoc position with a temporary contract for two years (1+1). Salary is competitive and ranges from €3,546 to €5,538 gross per month for a 38-hour week (scale 10, CAO-NU). A 0.8 FTE contract can be discussed. Additional employment benefits include sabbatical leave, study leave, partially paid parental leave, a year-end bonus of 8.3%, and an excellent pension scheme.
What's required
Applicants must have a successfully completed PhD in artificial intelligence, computer science, statistics, engineering, or a similar relevant field. Strong applied machine learning experience is required, with desirable background or interest in machine learning, computer vision, or time-series analysis. Experience with plant breeding or self-supervised learning is a strong plus. Candidates should be proficient in Python and familiar with PyTorch, Scikit-Learn, or similar modern ML libraries, and have experience with Git and HPC clusters as an advantage. Good scientific writing and communication skills are expected. English proficiency at C1 level is required, and an internationally recognized certificate of proficiency may sometimes be requested.
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