Optimization of digital models for estimating productivity and quality in greenhouses.
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Work description
Within the scope of the FIT4CEA project, INESC TEC will develop a robotic solution for monitoring operations in greenhouses, based on the Orioos robotic platform. The work will focus on the study, development, optimization, and validation of digital models capable of supporting the perception, agronomic analysis, decision-making, and operation of the robot in this type of environment. The activities will be developed in the context of INESC TEC's GreenTribe greenhouse and in greenhouses of FIT4CEA project partners, allowing the proposed approaches to be validated in real and distinct production scenarios.
Academic Qualifications
Master's degree in Agricultural Engineering or related field.
Minimum profile required
- Master's degree in Agricultural Engineering or related field.- Enrollment in a doctoral program.
Preference factors
- Experience in developing digital models for estimating productivity and quality in agricultural crops. - Knowledge of computer vision, image processing, machine learning, or deep learning. - Previous experience in precision agriculture, agricultural robotics, remote sensing, or agronomic data analysis.
Application Period
Since 30 Apr 2026 to 14 May 2026
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Centre
Robotics in Industry and Intelligent Systems