Robotics for Agriculture and Forestry
Work description
The work plan includes research, development, implementation, and validation of sensor fusion and machine learning algorithms for nutrient estimation in slurry, using spectral and conductivity information, including data processing, model calibration, comparison with reference laboratory analyses, and support for the experimental validation of sensors within the SMARTFERTILIZERS2Market project.
Academic Qualifications
Master's degree in Electrical and Computer Engineering or related field, with active enrollment in a doctoral program.
Minimum profile required
Master's degree in Electrical and Computer Engineering, or related fields;Active enrollment in a doctoral program;Knowledge of programming in Python and/or C++;Knowledge of signal processing, data analysis, or machine learning;Knowledge of sensory data acquisition and processing.
Preference factors
Experience in machine learning applied to sensory data; Experience in spectral signal processing, VIS-NIR, UV-VIS-NIR or optical sensors; Experience in calibration and validation of predictive models; Experience in sensor fusion;
Application Period
Since 21 May 2026 to 03 Jun 2026
Centre
Robotics in Industry and Intelligent Systems