Balanced fertilizers are essential for sustainable agricultural intensification. Widespread adoption of appropriate fertilizers requires a transformation of the fertilizer and food systems that must be driven by evidence-based agro-technical perspectives embedded in multi-stakeholder processes to create enabling conditions for adoption.

For stakeholders to be able to make sensible operational and strategic decisions, they need evidence-based information that is owned and shared by and with the stakeholders. The need for spatially explicit fertilizer recommendations to attain certain yield levels calls for the use of advanced crop-soil modelling and geo-spatial analyses. One of the challenges identified so far is the low fertilizer use efficiency and the vast spatial and temporal variability of crop response to fertilization.

It is in this context that IFDC is developing a Modelling and Mapping Team with staff, on the one hand, highly specialized in such advanced methodologies, and on the other hand can connect theoretical exercises with practical usability. IFDC is therefore seeking a scientist with hands-on experience in databases, crop-soil simulation modelling and their application in soil mapping with knowledge of statistical methods.

Scope of Work

• Execute the work activities under the supervision of the Modelling and Mapping Specialist and the Director.
• Support development of a database system
• Quality control database formats and data from experimental trial and survey data
• Understand and adapt crop-soil simulation models for country specific purposes
• Conduct analyses of fertilizer yield responses using advanced statistical, modelling and mapping techniques
• Teach in hands-on use of models and mapping
• Supervision of Master students in modelling and mapping
• Co-draft reports and scientific journal articles
• Travel in Ghana for field visits, teaching and meetings.

Qualification Required & Experience

• MSc/MPhil degree in agricultural sciences, agricultural engineering, soil science, geoecology
• Experience in crop growth-soil-water modelling and Decision Support System
• Good knowledge of crop physiology, plant nutrition and experience in statistical data analysis
• Knowledge of geographic information systems is an asset
• Excellent conceptualizing capabilities to link theoretical modelling and mapping approaches to help disentangle drivers for yield from practical experimental data
• Good Experience in data modelling via R/Python/Java Script or Julia languages programming and use of data manipulation and statistical packages Good communication skills and enjoyment of scientific teamwork.Ability to write project reports and scientific papers

Location: Accra

How To Apply For The Job

To submit your application, click on the link below and complete all relevant fields on the online application form.

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Closing Date: 30 December, 2022