Research Supervisor at IITA - International Institute of Tropical Agriculture

DUTIES:

• Generate calibration data for rapid, non-destructive estimation of dry matter and starch content using IoT devices developed under the NESTLER project.
• Develop statistical models to relate laboratory measurements with instrument measurements preferable using machine-learning approaches.
• Deploy IoT devices in breeding trials, cassava processors and farms to scale the technology and generate field-based validation data.
• Support implementation of pilot experiments involving deployment of weather and soil sensing stations at strategic locations in IITA cassava field trials in Nigeria. Specific activities related to this are:
  •  Sensing Station Setup to measure key environmental parameters relevant to cassava cultivation (rainfall, temperature, humidity, solar radiation, and soil moisture content).
  • Automate data collection through use of mobile network to enable a time-series dataset for analysis.
  • Integrating farm-level data from the research farms, such as planting methods, fertilizer usage, pest and disease management, and other relevant factors that may impact cassava yield.
  • Data analysis and model development using statistical analysis techniques and machine learning algorithms to identify patterns, correlations, and interactions between the environmental variables and cassava yield.
  • Model validation and iterative improvement to assess its accuracy and reliability.
• Contribute to other project activities including preparing reports, participation in project meetings, preparing communication materials.
• Perform any other job-related task as may be assigned by the Supervisors.

Requirements

QUALIFICATION:                        

BSc/HND in Plant Breeding, Agronomy or any other related field with a minimum of three (3) years’ experience performing a similar role in a well-structured environment.

COMPETENCIES:

The ideal candidate must:

• Be experienced in the use of statistical analysis techniques and database software.
• Be experienced in data analysis and interpretation.
• Be experienced in report writing.