Applications of resource-efficient technologies for a sustainable olive growing
Scientific-Disciplinary Group
07/AGRI-03 - Arboriculture And Forest Systems
Description
The contract includes research work that integrates proximal and remote sensing technologies with AI based decision support systems to optimize water, nutrient and fruit growth/maturation management and ultimately improve olive production efficiency and sustainability. The selected researcher will contribute to the development of predictive models and machine learning algorithms for data analysis from plant-based sensors, multispectral and thermal imagery, and IoT systems. The required skills include precision olive growing, olive tree physiology, proximal and remote sensing for assessing olive water and nutrient status as well as fruit growth/maturation, machine learning and computer vision techniques, statistical data analysis, and Python programming. Activities will include field calibration and validation of models and data integration into a decision support system.
Compensation
28,456 Euro
Job posting website
Number of positions
1
Maximum duration
24.0
Funding body
Università degli Studi di Palermo
How to apply
View the original posting on the MUR website: Go to MUR website