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- 31 Aug, 2029 PhD start date : Sep-Oct, 2026 Main partners: INRAE Clermont-Ferrand, France Poznan University of Technology, Poland Università degli Studi di Padova, Italy Università degli Studi di
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candidate will hold a PhD in geosciences, applied machine learning, data assimilation, or applied mathematics. The selection will be based on the following scientific and technical criteria: Experience in
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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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]. 3. Explore the diversity of signals and perform complementary experiments to finalize the training dataset [Month 6 – 12]. 4. Develop a data analysis process based on machine learning for multimodal
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for Horticulture and Phenotyping) team research topics focus on low cost computer vision and machine learning, simulation assisted plant phenotyping and machine learning based data mining for plant biology
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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point-based PhorEau projections using a machine-learning model predicting tree species richness as a function of spatially explicit abiotic and biotic covariates, including satellite-derived data