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PauloCityPiracicabaGeofield Contact State/Province São Paulo City São Paulo Website http://www.fapesp.br/oportunidades/ Street R. Pio XI, 1500 - Alto da Lapa Postal Code 05468-901 STATUS: EXPIRED X (formerly Twitter) Facebook
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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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Website http://www.fapesp.br/oportunidades/ Street R. Pio XI, 1500 - Alto da Lapa Postal Code 05468-901 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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Website http://www.fapesp.br/oportunidades/ Street R. Pio XI, 1500 - Alto da Lapa Postal Code 05468-901 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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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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Vaz) Contact State/Province São Paulo City São Paulo Website http://www.fapesp.br/oportunidades/ Street R. Pio XI, 1500 - Alto da Lapa Postal Code 05468-901 STATUS: EXPIRED X (formerly Twitter) Facebook
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Area, and coordinated by Professor Alfeu Joãozinho Sguarezi Filho. The research is part of an international research network and involves geospatial analysis, optimization and modeling, as