Postdoctoral Researcher in Multimodal Crop Analysis & Fertilizer Optimization

About the role

Mohammed VI Polytechnic University (UM6P), a research-and-innovation university in Morocco, is recruiting a postdoctoral researcher in its College of Computing (Benguerir campus). The project develops farmer-centric systems that fuse multi-modal remote sensing, soil and phenology data to enable crop classification and precise, customized fertilizer recommendations. The appointment is fixed-term (24 months).

Required profile

• PhD awarded or defended before the start in Computer Science, Remote Sensing/Geoinformatics, Agricultural Data Science or a related field.
• Strong track record in remote-sensing imagery and/or time-series analysis and machine learning/deep learning for spatio-temporal data.
• Ability to work independently and produce reproducible research outputs.
• Good written and spoken English and willingness to collaborate with agronomists and partners.
• Preferred: postdoc or at least 2 years of research experience after the PhD, first-author publications, experience with multimodal data fusion, satellite platforms (Sentinel, Landsat, GEE) and reproducible pipelines, and field or agronomic experience.

Required skills

• Advanced Python and experience with ML frameworks such as PyTorch and TensorFlow.
• Experience with geospatial tools such as rasterio and GDAL.
• Preferred: experience with multimodal data fusion, satellite platforms and reproducible pipelines.

To apply, submit a cover letter mentioning the CropID project and available start date, a CV with links (ORCID, GitHub), a 1–2 page research statement with a 12–18 month plan, up to 3 representative papers and links to code/datasets, and 2–3 referee contacts. Shortlisted candidates are invited to a technical interview; the appointment is fixed-term (24 months) at UM6P in Benguerir.