Postdoc in Integrated Agronomic – Genomic – Remote Sensing Data Fusion

Are you passionate about integrating agronomic, genomic, and remote sensing data to better understand plant stress, disease progression, and crop resilience? Do you enjoy working across field campaigns, laboratory analysis, and advanced data systems? Then this postdoctoral position within the ESA-funded HYDRA-EO project (ESA Tender ITT , Crop Multiple Stressors, Pests and Diseases) is an excellent opportunity for you.

HYDRA-EO focuses on the multi‑scale detection of biotic and abiotic stress in Mediterranean crops using UAV hyperspectral and thermal imagery, radiative transfer modelling, agronomic field measurements, and genetic markers. As a postdoctoral researcher, you will develop an integrated data framework that combines remote sensing observations, phenotypic measurements, and genomic datasets into a coherent analytical pipeline to support early disease detection and trait interpretation across the Netherlands, Italy, and Spain.

You will play a key coordinating role in the 2026 airborne and field campaigns in these countries, facilitating sampling plans, metadata protocols, genetic–phenotypic data integration, and communication between European partners.

• Integrate multi‑source datasets (remote sensing, agronomic traits, phenotyping records, and genomic markers) into a unified analytical framework.
• Conduct field scouting to identify biotic and abiotic stress symptoms in crops, coordinate sampling activities, and ensure accurate collection of phenotypic information across sites.
• Support the design, implementation, and coordination of UAV hyperspectral and thermal field campaigns in the Netherlands, Italy, and Spain.
• Process and harmonise phenotyping, genetic, and canopy‑level remote sensing measurements for multi‑stressor disease detection.
• Collaborate with plant physiologists, geneticists, and remote sensing specialists to link spectral traits with biochemical and genetic variation.
• Contribute to scientific publications, methodological reports, and data standards for HYDRA‑EO.
• Communicate effectively with international project partners and stakeholders to support coordinated data collection and field campaign planning.

You will be part of the Laboratory of Geo‑Information Science and Remote Sensing (GRS) at Wageningen University, collaborating closely with researchers working on hyperspectral imaging, radiative transfer modelling, machine learning, agronomy, and plant genetics. You will also work with HYDRA‑EO partners in the Netherlands, Spain, and Italy, contributing to multi‑scale crop disease studies and joint field campaigns.