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the analysis and monitoring of detected events within the continuous monitoring of the SIN. The fellow will be based at the State University of Campinas's Faculty of Electrical and Computer Engineering (FEEC
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Foundation (FAPESP), and combines statistical analysis, spatial methods, and qualitative research. Georeferenced data from the Military Police and the Municipal Secretariat of Urban Security will be used
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Experience in machine learning, math, and programming. LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers available1Company/InstituteUniverCountryBrazilState
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to apply Website http://www.fapesp.br/oportunidades/8911 Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Brazil Eligibility of fellows: country/ies
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WaterWeave project, which focuses on innovative solutions for monitoring and the sustainable management of water resources. The fellow will develop machine learning and cloud computing techniques to estimate
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and computer programming skills. The objective of this research is failure and damage detection in the petroleum artificial lift process using the operational data signal analysis (time series analysis
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machine learning (ML) algorithms to identify previously unknown correlations between synthesis parameters (inputs) and optical, electronic and chemical properties (outputs), such as quantum yield, light