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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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Immunodeficiencies), Faculty of Medicine (FM), University of São Paulo (USP), under the supervision of Prof. Dr. Maria Notomi Sato. Requirements: PhD in Immunology or a related field. Knowledge of virology, cellular
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on CV evaluation, will be contacted by email by April 13, 2026, to schedule an online interview. The position is open to Brazilian and international applicants. Proficiency in English and knowledge
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Educational background and field of knowledge: Agricultural Engineering/Agronomy or related fields, with a focus on Plant Pathology. Specific Requirements The candidate must hold a PhD degree with a thesis
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; - Proven experience in molecular biology techniques, clinical pathology, and translational research with human samples; - Basic knowledge or high motivation to work in bioinformatics and omics data analysis
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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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in engineering or a field related to the project; • Knowledge and proven expertise in computational optimization methods and discrete-event simulation, with experience in regular service design
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knowledge and advanced transfer learning techniques. The methodology incorporates fundamental radar wave propagation equations into the diffusion process, allowing for more accurate and physically consistent
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; - Supervise students. Requirements: • Fluency in English; • Experience with germination experiments and trait measurements; • Knowledge of statistics and data analysis using R; • Willingness to reside in Rio
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at the University of São Paulo's Museum of Zoology (MZUSP) in Brazil, strengthening of the taxonomic framework of the family in the Neotropical Region, and knowledge advancement of Brazilian biodiversity, while also