KU Leuven

Homepage: https://ees.kuleuven.be/en/bwb/research/land-surface-data-assimilation

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.

—- Responsibilities

Perform and disseminate high quality research related to soil moisture and biomass remote sensing, crop modeling, data assimilation and machine learning
Supervise master thesis students
For PhD students: follow training in line with the doctoral school requirements

—- Profile

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

Postdoctoral researcher:
PhD degree in Civil or Environmental Engineering, Bioscience Engineering, Hydrology, Meteorology, Remotely Sensed Earth Observation, Physics, Mathematics, Computer Sciences, or equivalent
Experience with land surface and/or atmosphere and/or crop processes and modeling
Experience with remote sensing, Earth observation, large datasets
Experience in statistics, including some notions on data assimilation
Experience with data-processing software such as Python, Matlab, IDL, GrADS, R, or other
Experience with programming and scientific computing in a language such as Fortran or C
Experience with high-performance computing in a Linux environment
Excellent motivation and grades
Creative, critical, analytical and innovative mindset
Ability to work independently and lead a small research group
Excellent written and oral communication skills in English, proven in publications
Experience with working with Git/Github is an advantage

—- Offer

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.

You can apply for this job no later than March 30, 2025 via the online application tool: http://www.kuleuven.be/eapplyingforjobs/light/60443187