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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
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dataset generation technique to optimize the training of neural networks (NNs) for seismic data prediction. The use of neural networks to predict seismic velocity models has shown increasingly accurate and
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models to improve seed-sowing strategies, assess long-term population sustainability, and support evaluations of cost-effectiveness and cost–benefit of the program. The project also emphasizes social
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potential use of the Tietê–Paraná Waterway. 3) Solving problems associated with the definition of regular navigation services. 4) Modeling and solving the lock transit scheduling problem. Requirements: • PhD
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. Knowledge in statistical modeling, data science, exploratory analysis, and natural language processing applied to legal texts and empirical legal studies is highly desirable. Candidates must have excellent
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vesicles (OMVs), exploring OMV-based cancer nanovaccines by using analytical approaches, cell culture systems, and animal models. The fellow will be based at CNPEM's Brazilian Biosciences National Laboratory
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of the project is to investigate how neuroinflammation and the protein annexin A1 modulate vulnerability and resilience in animal models of post-traumatic stress disorder. Applicants are expected to have prior
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2 years. MixForCarbon will assess the adaptation and initial productivity of about 30 land use models that include conventional forest species (Eucalyptus, Pinus, Rubber tree, among others) and non
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lipid–carotenoid interactions is required. Experience in in vivo models, extraction and quantification of bioactive compounds, industrial microbiology, and process development—preferably using green
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configurations hinders the creation of generalizable solutions for processing these images. This project proposes an innovative approach that combines state-of-the-art diffusion models with physical radar