National Expert on Drone-based Seeding, Plant Nutrient and Weed Management

Provide technical support for drone-based agricultural practices.

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FAO - Food and Agriculture Organization of the United Nations

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Application deadline 2 days ago: Friday 21 Aug 2026 at 21:59 UTC

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Overview

Provide technical support for drone-based agricultural practices.

You have:

  • A university degree (Bachelor's degree) in Remote Sensing, Geoinformatics/GIS, Agricultural Engineering, Precision Agriculture, Soil Science, or a closely related discipline.
  • A minimum of five years of professional experience in UAV-based remote sensing applications, including at least two years of experience in agricultural or precision agriculture applications.
  • Working knowledge (level C) of English.
  • National of Sri Lanka or resident of the country with a valid work permit.

Organizational Setting

The Food and Agriculture Organization (FAO) is a specialized agency of the United Nations that leads international efforts to eradicate hunger. FAO’s goal is to achieve food security for all by ensuring that people have regular access to sufficient, safe, and nutritious food to lead active and healthy lives. With 195 Members - 194 countries and the European Union, FAO operates in more than 130 countries worldwide. In Sri Lanka, FAO has been working since 1979 through its Representation (Country Office) in Colombo.

FAO contributes to the achievement of the 2030 Agenda through its Strategic Framework by supporting the transformation of agri-food systems to become more efficient, inclusive, resilient, and sustainable. This is guided by the Four Betters: Better Production, Better Nutrition, a Better Environment, and a Better Life, ensuring that no one is left behind.

Sri Lanka’s rice and other field crop (OFC) production systems are under increasing pressure from climate variability, labour shortages, rising input costs, and inefficient input use. Smallholder farmers commonly apply weedicides and fertilizers uniformly across their fields despite significant intra-field variability, resulting in reduced input-use efficiency and increased environmental risks.

Under TCP/SRL/4104, FAO is supporting the Department of Agriculture (DOA) in developing and field-validating performance-based, platform-agnostic standards and protocols for drone-based direct seeding, weed management, and nutrient management in a maize-mungbean cropping system in the Dry Zone. The project utilizes drone-acquired RGB and multispectral imagery to facilitate the early detection of weed infestations and nutrient stress, enabling targeted, site-specific input applications instead of conventional blanket treatments.

Reporting Lines

The National Expert on Drone-based Seeding, Plant Nutrient and Weed Management will work under the overall supervision of the FAO Representative for Sri Lanka and the Maldives, the direct supervision of the Assistant FAO Representative (Programmes), and the technical guidance of the Lead Technical Officer of the project. The incumbent will work closely with the relevant technical teams at the Field Crops Research and Development Institute (FCRDI) and other selected partner institutions.

Technical Focus

The objective of this assignment is to provide technical and operational support to FCRDI for the design, implementation, monitoring, evaluation, and validation of drone-based seeding, plant nutrient management, and weed management protocols for maize–mungbean cropping systems. The assignment will support the development of national standards and operational guidelines under project TCP/SRL/4104. The incumbent will provide technical and operational support to FCRDI for the UAV-based remote sensing components of the project, including supporting the processing and analysis of drone-acquired multispectral imagery, assisting in the validation of field data, and contributing to the development of operational protocols for weed and nutrient management for use by the Department of Agriculture's extension system and the national agricultural service-provider sector.

The incumbent will provide technical and operational support for the following activities: • Supporting the implementation of imagery-based components of the project, including weed characterization and management (Output 2). • Supporting activities related to nutrient deficiency detection and management (Output 3). • Assisting with impact assessments and economic viability analyses. • Supporting the delivery of capacity-building activities and the development of knowledge products.

Tasks and responsibilities

• Provide technical and operational support to the planning, establishment, and management of field trials for drone-based mungbean seeding, maize nutrient management, and maize weed management. • Assist in the identification and preparation of suitable research and demonstration plots in coordination with the Field Crops Research and Development Institute (FCRDI) and other relevant local stakeholders. • Support the development of field protocols and data collection methodologies to evaluate the agronomic, operational, and economic performance of drone-based applications. • Support the coordination of drone operations and assist in ensuring compliance with approved experimental designs and field protocols. • Collect, compile, and analyze field data on crop establishment, plant growth, nutrient status, weed suppression, yield performance, input-use efficiency, and operational costs. • Support the assessment and interpretation of drone-derived imagery and related datasets to inform decision-making and validate operational protocols. • Document field observations, lessons learned, implementation challenges, and opportunities for scaling up drone-based technologies. • Contribute to the development and refinement of national standards, technical guidelines, and operational protocols for drone-based applications in agriculture. • Provide technical and operational support to FCRDI in organizing stakeholder consultations, field demonstrations, and capacity-building activities for extension officers, researchers, and farmers. • Prepare technical reports, progress updates, and recommendations, and perform any other related duties as required...

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING

Minimum Requirements

• A university degree (Bachelor’s degree) in Remote Sensing, Geoinformatics/GIS, Agricultural Engineering, Precision Agriculture, Soil Science, or a closely related discipline. • A minimum of five years of professional experience in UAV-based remote sensing applications, including at least two years of experience in agricultural or precision agriculture applications. • Working knowledge (level C) of English. • National of Sri Lanka or resident of the country with a valid work permit

FAO Core Competencies

• Results Focus • Teamwork • Communication • Building Effective Relationships • Knowledge Sharing and Continuous Improvement

Selection criteria

• Master’s degree or PhD is an asset • Proficiency in GIS software, such as QGIS or ArcGIS, for producing georeferenced prescription maps and other decision-support products. • Demonstrated hands-on experience in multispectral image acquisition, radiometric calibration, and image processing using software such as DJI Terra, Pix4Dfields, Agisoft Metashape, or MicaSense Atlas. • Experience in designing and analysing field calibration studies that relate vegetation indices to ground-truth agronomic data. • Experience in delivering technical training for extension officers, researchers, and farmer groups. • Excellent command of written and spoken English. Working knowledge of Sinhala and/or Tamil is required.

Potential interview questions

Describe a successful project where you utilized UAV technology in agriculture. What were the outcomes? This question evaluates your practical experience with drone applications in agriculture. Discuss the project details, your role, and how UAV technology improved agricultural practices.
How do you approach data analysis from drone-acquired imagery? This assesses your analytical skills and familiarity with processing drone data. Pro members can see the explanation.
Can you elaborate on a time when you had to train others on drone technology? What challenges did you face? Pro members can see the explanation. Pro members can see the explanation.
What strategies would you use to increase input-use efficiency in crop production? Pro members can see the explanation. Pro members can see the explanation.
Describe your experience in conducting field trials for agricultural practices. What key factors do you consider? Pro members can see the explanation. Pro members can see the explanation.
How do you handle discrepancies when analyzing field data? Pro members can see the explanation. Pro members can see the explanation.
What potential challenges do you foresee in implementing drone technology in Sri Lankan agriculture? Pro members can see the explanation. Pro members can see the explanation.
How do you ensure compliance with agricultural standards in your projects? Pro members can see the explanation. Pro members can see the explanation.
Added 16 days ago - Updated 2 days ago - Source: fao.org