International Scientist- Spatial Data Science and GIS – K4GGWA at - Nairobi, Kenya - World Agroforestry Centre (ICRAF)

Description

The World Agroforestry Centre, is an international institute headquartered in Nairobi, Kenya, and founded in 1978. The Centre specializes in the sustainable management, protection and regulation of tropical rainforest and natural reserves.
Summary

Under the supervision of the head of SPACIAL and the Co-lead for the Knowledge for Great Green Wall (K4GGWA) project in West Africa, the Spatial Data Scientist and GIS expert will focus primarily on GIS analysis tasks, supporting the K4GGWA project team.

Tasks will include engagement with partners and project stakeholders across GGW countries, including the Pan African Agency and UNCCD Accelerator.

Spatial data science and GIS tasks will include data analysis and mapping using QGIS, R Statistics or Python, particularly in relation to the mapping and monitoring of land health indicators.

Other tasks will include identification of data analytics problems, cleaning, and validation of data to ensure accuracy, completeness, and uniformity.

The position will also engage with multiple themes and units within CIFOR-ICRAF on scientific project tasks, particularly around access to and use of spatial data, database development and management, report writing, and scientific publications.

Finally, the position will contribute significantly to capacity development of regional and national GGW bodies and stakeholders to assess, map and monitor a wide range of biophysical and land health indicators.

Summary of responsibilities

Spatial analysis and mapping (GIS) using existing data at country and regional level, including from GGW partner countries and agencies.

Support project activities to strengthen the capacity of regional and national GGW bodies and stakeholders to assess, map and monitor a wide range of biophysical and land health indicators; responding to country needs, including to track the effectiveness of land restoration implementation, target interventions, and to guide policy; use of a wide range of available tools, including citizen science apps and relevant FAO.

Basic remote sensing analysis such as calculations and analysis of vegetation indices and land cover classes.

Support in the development and deployment of machine learning models using ground truth and remote sensing data to assess various aspects of ecosystem health at scale.

Contribute to the preparation of annual state of land (use change, health, incl. trends in climate) and vegetation maps, and knowledge products, building on existing tools and analysis, where relevant, including the EU's 'Africa Knowledge Platform'.
Represent CIFOR-ICRAF at conferences and/or meetings from a technical remote sensing / data science perspective.
Manage spatial data science fellows and interns as needed.

Requirements

MSc in GIS, spatial data science or related field.
Some background in remote sensing, whether from satellite or from aerial/drone imagery.
High level of proficiency in QGIS, some experience with computer programming languages such as R or Python.
Experience in handling spatial data.


Personal attributes and competencies:
Experience with interactive decision support systems (eg. dashboards).
Fluent in French and strong English writing and presenting skills