Robotics for Agriculture and Forestry
[Open soon]
Work description
The work plan includes the analysis of data generated by agricultural robots and IoT devices, the definition of methodologies for their integration into decision support systems, and the exploration of machine learning techniques focused on agronomic problems. It will also involve linking engineering, robotics, IoT, and agronomy teams, promoting the transformation of collected data into useful indicators for end users. The work will also include supporting the preparation of applications for national and European projects, namely through the identification of opportunities, definition of technical concepts, agronomic framing of solutions, and contributing to the technical writing of proposals. Where applicable, the candidate may also support real-world validation activities, analysis of experimental results, technical project reports, and preparation of documentation associated with knowledge transfer.
Academic Qualifications
PhD in Agricultural Sciences, with a Bachelor's and Master's degree in Agricultural Engineering.
Minimum profile required
PhD in Agricultural Sciences;Bachelor's and Master's degrees in Agronomic Engineering or related field;Experience in applying machine learning techniques to agronomic data;Experience in analyzing, interpreting, and evaluating data to support decision-making in agriculture;H-index greater than 8.
Preference factors
Experience in using machine learning techniques applied to agriculture; Experience in preparing, managing, or reporting on research and innovation projects; Experience in preparing applications for national and European projects; Knowledge of decision support systems in an agricultural context; Experience in digital agriculture, sensors, IoT, agricultural robotics, or field data analysis; Ability to work interdisciplinarily with teams in engineering, robotics, information technology, and agronomy.
Application Period
Since 16 Jul 2026 to 29 Jul 2026
[Open soon]
Centre
Robotics in Industry and Intelligent Systems