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expenses Duration: 36 months, with the possibility of an international exchange period Workload: Full-time (40 hours per week) Expected start date: April 2026 Requirements: • PhD in Chemical Engineering
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Documentation: 1. Cover Letter (Letter of motivation); 2. Copy of PhD Thesis; 3. Updated Curriculum Lattes (or CV for international candidates); 4. Contact information for up to three references
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with a PhD in Biology, Ecology, Geosciences, Earth System Science, Environmental Sciences, or related fields and proven experience in computational modeling of vegetation to conduct research
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. Duration The fellowship is granted for 36 months. 4. Eligibility and Requirements • PhD obtained within the last 4 years or by May 31st; • Background in IR image analysis and experimental phase change
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an ethnographic approach and actively collaborate with social movements and IEE-USP, strengthening existing connections. Requirements: PhD completed; fluency in English; experience with qualitative methods
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Claro and travel to Cavalcante (fieldwork); • Consistent scientific output; • PhD completed within the last 7 years. Interested candidates should complete the Google form (https://forms.gle
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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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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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qualitative nature of the methodology to be developed, which requires dialogue between the researcher and the research subject. To learn more about the proposal, request further information by email at