79 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions in Brazil
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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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Experience in machine learning, math, and programming. LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers available1Company/InstituteUniverCountryBrazilState
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. Full call for applications: https://drive.google.com/file/d/1S2g1B6UWyTH0mc5vA75o5cTG2-e2zr1p/view?usp=sharing . This opportunity is open to candidates of any nationality. The selected candidate will
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preparation for use in AI models; - Experience with explainability techniques for Machine Learning models; - Desirable experience with system modernization. To apply, send an email with the subject “Inscrição
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which should be spent on items directly related to the research activity. More information about the fellowship is at: fapesp.br/oportunidades/9075 . Where to apply Website http://www.fapesp.br
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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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(FCT-UNESP) in Presidente Prudente – but the selected candidate must be open to working and communicating with all researchers on the team (see https://bv.fapesp.br/en/auxilios/118867 ) The selected
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on eligibility and benefits is available at: https://fapesp.br/en/postdoc . More information about the fellowship is at: fapesp.br/oportunidades/8978 . Where to apply Website http://www.fapesp.br/oportunidades
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. International experiences obtained during undergraduate or master’s studies will not be considered. Required Documents (submitted exclusively via online form): https://forms.gle/sLQoPsXYV5dRM8VG9 a. Curriculum
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learning and community engagement in conservation. Requirements: PhD completed; fluency in English; experience with qualitative methods; experience with and availability for fieldwork, in accordance with