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techniques—particularly convolutional neural networks (CNNs)—will be applied to identify complex canopy patterns and classify successional stages. Mandatory requirements: Ph.D. in Remote Sensing, Forest
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addition to supporting field and laboratory activities. They will integrate Net Primary Production (NPP) and the Gross Primary Production (GPP) data to construct a reference carbon budget and assess initial responses
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journals; - Participate in the life of the Center, contributing to scientific meetings; - Develop collaborations within the CBG network; - Offer short courses or minicourses; - Interact with graduate
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reputable international journals; - Participate in the life of the Center, contributing to scientific meetings; - Develop collaborations within the CBG network; - Offer short courses or minicourses
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Studies), it examines the role of private companies, their relations with the public sector, and governance disputes. Activities The postdoc will map sociotechnical networks, analyze actors, and produce
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staff position within a Research Infrastructure? No Offer Description Development of silicon carbide (SiC) semiconductor technologies for quantum bits based on controlled surface and interface defects
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staff position within a Research Infrastructure? No Offer Description This research project aims to develop a synthetic dataset generation technique to optimize the training of neural networks (NNs
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), Multilayer Perceptron (MLP), Autoencoders, Convolutional Neural Networks (CNNs), and Kolmogorov–Arnold Networks (KANs). Desirable knowledge of Gradient Boosting models such as HistGBM, LightGBM, and XGBoost
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staff position within a Research Infrastructure? No Offer Description Title: “Synthetic Dataset Generation Technique to Optimize Neural Network Training for Seismic Data Prediction” Research Area
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, supporting monitoring and impact evaluation of the PCJ Basin Plan, with emphasis on environmental education and water loss control in supply systems. Application: send documents in one PDF to nups@eesc.usp.br