Overview
The role involves providing day-to-day technical support on Earth Observation (EO) workflows and ensuring the timely delivery of geospatial products for landcover analysis and monitoring. It also includes coordinating field validation activities and strengthening national capacities.
Tasks Summary
- Provide day to day technical support to SLCO on AIMS workflows and ensure timely delivery of geospatial products for landcover analysis and monitoring under the EU funded projects, including NNTALD and WAPNP projects.
- Coordinate with AIMS HQ to align priorities, resolve technical issues, and integrate EO insights into programme planning and reporting.
- Support ground‑truthing missions and validation of land‑cover and forest‑cover assessments.
- Work with partners to ensure consistent, high‑quality field data collection for validating EO‑based land‑cover monitoring.
- Deliver training to CO staff, government partners, and eco‑guards on geospatial tools and the project geospatial platform.
- Organize webinars and workshops jointly with the CO programme team to present AIMS findings within WFP and externally.
- Represent AIMS in technical working groups and NN‑TALD governance structures.
- Review AIMS data‑collection and verification tools, as well as the reporting system, and provide constructive feedback and recommendations.
- Participate in biannual AIMS in-person meetings at HQ for professional development.
- Perform additional tasks as required to support AIMS operations, NN‑TALD implementation, and geospatial analysis activities.
- Perform other duties as assigned.
Experience Requirements
- Experience in geospatial analysis, geo-information management, analysis, and processing of VHR imagery.
- Familiarity with ecosystem restoration, regenerative design and agricultural projects, their types, scope, and expected outputs.
- Proven proficiency in modern high‑level programming languages and analytical environments, particularly R and Python for processing geospatial and geophysical data.
- Experience applying Machine Learning (ML) and Artificial Intelligence (AI) techniques to geospatial or Earth Observation workflows.
- Good presentation and team working skills, with the ability to follow and develop a given scope of work.
- Experience in early warning and remote sensing (interpretation and analysis) and expert knowledge of GIS software (ARC GIS, Q-GIS) and analytical methodologies.
Qualification Requirements
Advanced University degree in physical geography, biology, physics, or related field
