PhD or Postdoctoral fellow in satellite remote sensing and data assimilation applied to agricultural production

KU Leuven is looking for an enthusiastic PhD or Postdoctoral researcher with a heart for plant-soil interactions and food security, and interest or expertise in satellite-based remote sensing and modeling. The candidate will aim for (i) crop modeling at the field to continental scale, (i) satellite data assimilation using the AquaCrop model embedded within NASA’s Land Information System (LIS), (iii) machine learning to estimate soil moisture and biomass based on microwave signals (Sentinel-1, NISAR, SMOS, SMAP), (iv) quantifying the impacts of past climate extremes and projected climate change on crop yields around the world. The research will participate in cutting-edge and international research to improve estimates of agricultural production. You will be part of the KU Leuven Department of Earth and Environmental Sciences, Division Soil and Water Management, in the dynamic research group “Land Surface Remote Sensing, Modeling and Data Assimilation” (prof. Gabriëlle De Lannoy), and you will collaborate with the VUB “Water and Climate Department” (prof. Wim Thiery) and TU Delft (prof. Susan Steele-Dunne). The researcher is expected to work in a broad international context within the CROPWAVES (Belspo) project, collaborate with other researchers and students, and should be willing to contribute to open source code distribution (e.g. GitHub).

The pressure of population growth and climate change ask for innovative solutions to monitor crop growth at the continental scale. Remote sensing and high performance computing allow to address this need, but the interpretation of active and passive microwave signals in terms of crop development, and the implementation of physically-based crop models such as AquaCrop at the continental scale are only in their infancy. Our team is committed to maximally extract geophysical information from active and passive microwave sensors, and to advance the large-scale use of physically-based land surface and crop models at increasing spatial resolutions. In particular, our department has a long history of development and maintenance of the AquaCrop crop model. At the same time, machine learning using satellite data offers new opportunities to estimate biomass and these might help to improve or complement our physically-based models.

PhD student:

• MSc degree in Bioscience Engineering, Civil or Environmental Engineering, Hydrology, Meteorology, Remotely Sensed Earth Observation, Physics, Mathematics, Computer Sciences, or equivalent
• Excellent motivation to work on soil-plant processes, remote sensing and modeling
• Experience with data-processing or programming in Python, Matlab, IDL, GrADS, R, or other
• Interest in open source code distribution (e.g. GitHub)
• Excellent motivation and grades
• Creative, critical, analytical and innovative mindset
• Ability to work independently
• Excellent written and oral communication skills in English

• EITHER: fully funded PhD scholarship for 4 years; support and training through the Arenberg Doctoral School (https://set.kuleuven.be/phd); students graduating with a Msc degree in the summer 2025 are encouraged to apply
• OR: postdoc position for 2 years, with a possibility for 1 year extension
• The start date can be negotiated, but no later than the summer-early fall of 2025.
• Competitive salary, support in career development
• Multi-disciplinary and international professional environment
• Leuven is a charming historical university town, located in the heart of Western Europe

Only scientists matching the above profile should apply. Please submit your resume, along with a motivation letter and two names for references via the online application tool. Applicants for a PhD position, please make sure to indicate your study grades (obtained until now) in your resume. For more information please contact prof. dr. ir. Gabrielle De Lannoy, tel.: +32 16 37 67 13, mail: gabrielle[dot]delannoy[at]kuleuven[dot]be.

 

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