Postdoctoral Research Fellow at icipe - International Centre of Insect Physiology and Ecology

Overall purpose of the job
The successful applicant will be responsible for: 
Conducting dynamic and cutting-edge research in geospatial and remote sensing modelling for 
monitoring robusta coffee pests and diseases.
Contributing to the understanding of the distribution and the seasonal dynamics of the robusta coffee 
and other tree interactions in coffee agroforestry systems.

VACANCY ANNOUNCEMENT
(Ref. No. IRS/489/042022)

• Geospatial characterisation of the robusta coffee agroforestry systems in Uganda.
• Specific duties
• The successful candidate is expected to:
• Acquire multi-source remotely sensed data for monitoring and modelling of robusta coffee pests and 
• diseases.
• Design and use open data collection technics/ tools to gather field observations on Robusta coffee 
• pests and diseases.
• Predict the current epidemic risk evaluation (dynamic maps) for major robusta coffee pests and 
• diseases in Uganda. 
• Simulate (through modelling) the future robusta coffee pest and disease risk according to various 
• climate change scenarios.
• Characterise robusta coffee agro-system at a landscape scale using optical and radar satellite systems 
• of different spatial resolutions.
• Estimate the robusta coffee landscape structure metrics using geospatial modelling techniques.
• Provide geospatial information that contributes to the designing of the integrated pest management 
• (IPM) strategy of robusta coffee pests.
• Actively engage in resource mobilisation and proposal development.

Requirements/qualifications

• PhD in Geoinformation and Earth Observation, Environmental Sciences, Ecology, or any related field 
• with an emphasis on GIS, remote sensing, and geospatial modelling.
• Extensive knowledge and experience in ecological niche modelling.
• Experience in using optical and radar satellite systems. 
• Demonstrated experience in crop and yield modelling.
• Demonstrated experience in the use of Google Earth Engine and R programming language.
• Experience in designing and using open data collection tools for field data collection.
• Experience in working in dynamic landscape systems.
• Excellent publication track record. 
• A high degree of organisation, adaptability, and prioritisation.
• Experience in capacity building through mentorship of MSc and undergraduate students.
• Excellent communication skills.

Core competencies

• Demonstrated experience in ensemble species distribution modelling.
• Experience in processing and analysing ‘big’ satellite data using semi-automated procedures.
• Experience in modelling different insect pest dynamics.
• Reporting
• This position reports to the Research Scientist, Data Management Modelling and Geoinformation (DMMG) Unit