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World Agroforestry Centre (ICRAF)
Data/Research
Description
Requirements
- MSc in Agronomy/Crop Physiology & Remote Sensing
- Minimum 3–5 years of experience in applied agricultural research
- Demonstrated experience integrating field trials, physiological measurements, and remote sensing data
- Strong quantitative and data analysis skills (e.g., R, Python, GIS platforms, Google Earth Engine, ArcMap)
- Experience working in multi-disciplinary and multi-location projects
- Prior engagement with international, CGIAR, NARS, or donor-funded programs is an advantage
Responsibilities
Agronomy
- Design, implement, and oversee on-station and on-farm agronomic trials aligned with breeding and seed systems research objectives
- Optimize agronomic packages (plant population, nutrient management, water management, and cropping systems)
- Ensure standardized agronomic protocols and data quality across locations
- Monitor crop growth and field conditions, ensuring uniformity and trial integrity
- Maintain accurate agronomic records for all trials
- Analyze agronomic trial data and contribute to interpretation of G×E×M interactions.
Crop Physiology
- Identify and quantify key physiological traits associated with yield, stress tolerance, and resource-use efficiency
- Support phenotyping for drought, heat, nutrient stress, and other priority constraints through implementation of standardized phenotyping protocols across sites and seasons
- Integrate physiological trait data with agronomic and breeding datasets to inform varietal selection and targeting
- Conduct physiological experiments under field and controlled conditions (where applicable/necessary)
Remote Sensing and Geospatial Analytics
- Deploy and operate remote sensing tools such as UAVs/drones, handheld sensors, and proximal platforms for data collection, including processing, and analysis of imagery and sensor data
- Acquire & process imagery from satellites, drones, and aerial platforms
- Apply vegetation indices and spatial analytics for crop monitoring, stress detection, and trial quality assessment
- Integrate remote sensing and GIS data with field and physiological data for high-throughput phenotyping
- Produce spatial maps, dashboards, and visual products for technical reporting
- Mapping potential distribution area of various stresses, diseases and pests using environmental variables associated with their occurrence
Integration, Capacity Building, and Reporting
- Synthesize agronomic, physiological, and remote sensing evidence into actionable recommendations
- Provide technical backstopping and training to partners, field teams, and national programs
- Contribute to scientific publications, technical reports, and donor deliverables
- Support data documentation, reproducibility, and knowledge management
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