Must also have three 3 years of experience i programming in Python andor R; ii developing and implementing statistical, machine and deep learning models including PCA, PLS, SVM and ANN to leverage data from IoT sensors, remote and proximal sensing systems such as UAV, satellite, ground based, hand held and wearable imaging platforms to drive automated phenotyping pipelines for applications in agricultural crop production or improvement; iii designing and building out aspects of spatial and nonspatial data analytics, visualization and modeling related to IoTs, Cloud computing, and next generation sensors applied to smart greenhouse; iv applying spectroscopy computer vision imaging technologies, including RGB, NIR, multispectral, hyperspectral, thermal, LIDAR, to study plant phenotypic traits and spectral responses; v using highresolution aerial image data, hightemporal satellite imagery, environmental data layers and infield sensor data to evaluate RD material; and vi driving product placement recommendations as well as developing AI environmental classification models for sustainability modeling and crop yield predictions.br br Experience can be concurrent.br br Note Since there is no experience required in H.6, the Kellogg language is not required.
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