80 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Postdoctoral research jobs 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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position within a Research Infrastructure? No Offer Description Activities The fellow will be expected to research the relationship between these technologies (big data, machine learning, and the entire
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involve developing an approach that uses Knowledge Organization (KO) metadata and ontologies to optimize parallel processing and scheduling policies (via Kubernetes) for Machine Learning tasks. The fellow
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available for full-time dedication. How to apply: Applications must be submitted by April 30, 2026, via email to cpodv.fflch@usp.br (copy to megiani@usp.br ). For full details, please visit: https
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to apply Website http://www.fapesp.br/oportunidades/9351 Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Brazil Eligibility of fellows: country/ies
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. Where to apply Website http://www.fapesp.br/oportunidades/9337 Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Brazil Eligibility of fellows: country
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research contingency fund, equivalent to 10% of the annual value of the fellowship which should be spent on items directly related to the research activity. Where to apply Website http://www.fapesp.br
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be spent on items directly related to the research activity. Where to apply Website http://www.fapesp.br/oportunidades/9344 Requirements Additional Information Eligibility criteria Eligible destination
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. Familiarity with frameworks such as TensorFlow and Keras, as well as libraries including Scikit-learn, NumPy, and pandas; - Experience with machine learning models such as Extreme Learning Machine (ELM