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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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these images. This project proposes an innovative approach that combines state-of-the-art diffusion models with physical radar knowledge and advanced transfer learning techniques. The methodology incorporates
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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
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policies that promote forest systems resilient to environmental stresses. Requirements: • PhD in Forest Engineering, Agronomic Engineering, or related areas; • Experience in multifunctional forests and
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topics associated with infrared physics, such as celestial holography and related subjects. Applicants should hold a PhD in Physics and have a strong background in scattering amplitudes in gauge theories
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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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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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Applicants must hold a PhD degree obtained within the last 7 (seven) years prior to the start of the fellowship, from a recognized higher education or research institution in Brazil or abroad, with relevant
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-industrial residues from Brazil and Chile. The candidate must hold a PhD in Biotechnology, Pharmacy, Food/Chemical/Bioprocess Engineering, or related fields. Proven expertise is expected in chromatographic
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Paulo state, Brazil); - PhD degree obtained within the last three years in Botany, or related fields, with a dissertation focused on Plant Anatomy; - Availability to start activities as soon as the