The International Institute of Tropical Agriculture (IITA), a non-profit institution focused on agricultural innovations to address challenges like hunger, malnutrition, poverty, and resource degradation in Africa, is seeking an Individual Consultant specializing in Computational Modeling.
This consultancy role focuses on enhancing and generalizing existing machine-learning models used in agricultural systems and environmental monitoring, with a strong emphasis on improving computational performance, robustness, and reproducibility for complex, multi-crop, and multi-scenario applications.
Scope of Work / Key Responsibilities
The consultant will be responsible for, but not limited to, the following:
- Produce fully refactored and modularized machine‑learning modelling scripts with improved architecture, abstraction, and parameterization.
- Optimize codebases by removing redundant routines and enhancing computational performance and reproducibility.
- Generalize modelling workflows to support multi‑crop, multi‑location, and multi‑scenario applications.
- Integrate empirical modelling frameworks to strengthen predictive performance and model robustness.
- Incorporate additional spatial covariates to improve explanatory power and computational efficiency.
- Prototype AI‑enabled or agent‑based agronomic decision‑support workflow integrations to enhance reasoning, automation, and recommendation quality.
- Develop comprehensive technical documentation, including annotated code, methodology notes, and workflow descriptions.
- Prepare periodic progress reports reflecting milestones and technical achievements.
Required Qualifications and Experience
- Advanced degree (master’s or Ph.D.) in Agricultural Systems Modelling, Environmental Modelling, Data Science, Artificial Intelligence, or any related discipline.
- Minimum of five (5) years of relevant professional experience, preferably in forest carbon assessment or ecosystem monitoring.
- Demonstrated expertise in GIS, remote sensing, carbon accounting and other quantitative methods.
- Proven track record of scientific publications in forest inventory and tree carbon assessment.
- Experience mentoring graduate students, facilitating training, and contributing to capacity building.
- Strong analytical, communication, and scientific writing skills.
- Previous experience working with international organizations, donor-funded projects, or research institutions will be an added advantage.
