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Institute for Advanced Studies, University of São Paulo, São Paulo / FAPESP (BIOTA SYNTHESIS – Nucleus of Analysis and Synthesis of Nature-Based Solutions) | Brazil | 2 months ago
postdoctoral fellow to be part of a "Center of Analysis and Synthesis of Nature-based Solutions" (https://biotasintese.iea.usp.br). The Center is funded by the São Paulo Research Foundation (FAPESP) for a 5-year
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and Stakeholders – Development, execution, and analysis of surveys – supervision: Prof. Ricardo Corrêa Gomes (2) Communication and Stakeholders – Development, execution, and analysis of experiments
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) PhD in High Energy Physics and have experience in HEP data analysis workflow (computer modeling generation, reconstruction, etc.), including modern programming languages like Python and C++. Good
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statistical analysis. Candidates must send their CV for analysis, after which the pre-selected candidates will be interviewed. This opportunity is open to candidates of any nationality. The selected candidate
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process includes document analysis and interviews with pre-selected candidates. Applicants must submit a curriculum summary (FAPESP model - https://fapesp.br/sumula ), a motivation letter highlighting
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expertise in mathematical modeling applied to agriculture, environmental data analysis, and remote sensing. Activities will take place at the University of São Paulo's Luiz de Queiroz College of Agriculture
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staff position within a Research Infrastructure? No Offer Description We are offering a post-doctoral fellowship linked to the Thematic Project “Multidimensional Analysis of Language, Discourse, and
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candidates who have knowledge in this area of research on advocacy coalition framework, discourse network analysis and other quantitative methods. Experience in data science, R language, and artificial
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computing infrastructure and its components, and to design algorithms for the decision-making on how to choose the best level of the hierarchy to run each task/application component according to several
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statistics, global numerical modeling, analysis of large datasets, and seasonal and/or subseasonal forecasting. Fellowship: Open to candidates of all nationalities with a Ph.D. obtained by the start of