77 developer-"https:" "https:" "https:" "Lawrence Berkeley National Laboratory Physics" Postdoctoral research jobs in Brazil
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for Research and Guidance on Visual Impairment (CPODV), a Science Center for Development (SCD) based at the University of São Paulo's Faculty of Philosophy, Letters and Literature, and Human Sciences (FFLCH-USP
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position within a Research Infrastructure? No Offer Description Activities: This research investigates the use of artificial intelligence in developing data visualization systems for born-digital collections
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position within a Research Infrastructure? No Offer Description Activities: The post-doctoral fellow at the Aeronautical Technology Institute (ITA) in São Paulo state, Brazil, will work on the development
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of land use and climate change on the ecohydrological balance and, consequently, on water security. Activities: The activities involve the development and analysis of environmental, climatic, and land-use
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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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writing, Portuguese proficiency, good English, proactivity, and teamwork. The fellow will contribute through systematic literature review, indicator development and validation, and database organization
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of technical reports; and v) Production of scientific papers to be submitted to high-impact national and international journals, aligned with the objectives of the Science Center for Development in Digital
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staff position within a Research Infrastructure? No Offer Description Development of silicon carbide (SiC) semiconductor technologies for quantum bits based on controlled surface and interface defects
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Paulo state, Brazil, to work on the FAPESP Thematic Project entitled “Integrated Development of Biorefinery and Sugarcane Bioethanol Plant with Net-Zero CO2 Emissions: Pathways to Convert Renewable
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staff position within a Research Infrastructure? No Offer Description This research project aims to develop a synthetic dataset generation technique to optimize the training of neural networks (NNs