Remote Sensing Scientist
Lead and support interdisciplinary research for development (R4D) projects focused on applying remote sensing, GIS, AI, and geospatial analytics applications to improve water resources management, irrigation efficiency, agricultural productivity, and climate resilience in arid and saline environments.
Skills
About This Role
Job Summary
Lead and support interdisciplinary research for development (R4D) projects focused on applying remote sensing, GIS, AI, and geospatial analytics applications to improve water resources management, irrigation efficiency, agricultural productivity, and climate resilience in arid and saline environments.
Job Responsibilities
- Lead research on the application of GRACE/GRACE-FO, InSAR, GIS, and Earth Observation data for groundwater monitoring, aquifer sustainability assessment, and water resources management.
- Apply remote sensing techniques for land use/land cover mapping, salinity assessment, drought monitoring, evapotranspiration analysis, and agricultural water productivity evaluation.
- Develop AI- and machine learning-based decision support tools for water management, precision agriculture, and irrigation scheduling.
- Support the integration of satellite data and geospatial analytics into hydrological and agricultural modeling frameworks.
- Provide technical support in data analytics, spatial database management, and interpretation of remote sensing products across ICBA research programs.
- Contribute to proposal development and implementation of national and international research projects.
- Contribute to training programs, workshops, and capacity-building activities in remote sensing and water management.
- Publish scientific papers, technical reports, and policy-relevant outputs.
Qualifications and Experience
- *Essential*
- PhD in Remote Sensing, Geoinformatics, Hydrology, Water Resources, or related fields.
- Minimum 5 years of experience in applying remote sensing technologies for water management.
- Strong experience in Earth Observation applications, hydrological analysis, and geospatial modeling.
- Experience with GRACE/GRACE-FO, InSAR, satellite imagery analysis, and geospatial indices related to hydrology and agriculture.
- Experience in AI, machine learning, and spatial data analytics.
- Proficiency in programming and data analysis tools such as Python and R.
- Experience working as a member of a multidisciplinary team
- Excellent written and spoken English communication skills.
- *Desirable:*
- Experience in water resources and irrigation management in arid and saline environments.
- Experience with big data processing, cloud computing platforms, and geospatial data management.
- Knowledge of decision support systems and digital agriculture applications.
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