81 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " 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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: Artificial intelligence applied to seismics, neural networks, machine learning, synthetic data generation, seismic inversion, geological CO2 storage. Abstract: This research project aims to develop a synthetic
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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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information about the fellowship is at: fapesp.br/oportunidades/9059 . Where to apply Website http://www.fapesp.br/oportunidades/9059 Requirements Additional Information Eligibility criteria Eligible
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fellowship is at: fapesp.br/oportunidades/9064 . Where to apply Website http://www.fapesp.br/oportunidades/9064 Requirements Additional Information Eligibility criteria Eligible destination country/ies
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is at: fapesp.br/oportunidades/9073 . Where to apply Website http://www.fapesp.br/oportunidades/9073 Requirements Additional Information Eligibility criteria Eligible destination country/ies
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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