Scientist in Machine Learning for Proximal Soil Sensing (m/f/d)
I4S is a joint research project within the scope of the BonaRes initiative funded by the German Federal Ministry of Science and Education (BMBF). I4S develops and integrates several close-range soil sensors for assessing chemical and physical soil parameters related to soil fertility. Information derived from the data of these sensors is used as input for dynamic soil-plant models and a decision support system. The ultimate goal is to help farmers managing within-field heterogeneity of soils in order to improve yields and reduce environmental impacts. In the project a wide range of sensors are used for soil mapping including UV, Vis, NIR, MIR, XRF, LIB, gamma ray, and THz spectrometers which produce a large amount of data in terms of samples (n) and parameters (p). It is intended to use machine learning to establish calibration models that can predict important soil properties from the readings of these sensors. The scientific challenge consists in the heterogeneity of soil, sensor noise, spatial correlation, and relative low number of reference samples.
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Sept 17-20, 2019
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