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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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optimization in distributed systems. The work also involves modern compiler infrastructures, with emphasis on MLIR, and contributions to LLVM and the OpenMP standard. Applicants must hold a PhD in Computer
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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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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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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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Python and R; - Demonstrable experience with Machine Learning; - Excellent problem-solving skills and the ability to work both independently and as part of a team. This position is for full-time, on-site
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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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Experience in machine learning, math, and programming. LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers available1Company/InstituteUniverCountryBrazilState
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Educational background and field of knowledge: Agricultural Engineering/Agronomy or related fields, with a focus on Plant Pathology. Specific Requirements The candidate must hold a PhD degree with a thesis
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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